439 Publications

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[439]
2024 | Journal Article | LibreCat-ID: 53073
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, Proceedings of the AAAI Conference on Artificial Intelligence 38 (2024) 14388–14396.
LibreCat | DOI
 
[438]
2023 | Preprint | LibreCat-ID: 44512 | OA
Detecting Novelties with Empty Classes
S. Uhlemeyer, J. Lienen, E. Hüllermeier, H. Gottschalk, ArXiv:2305.00983 (2023).
LibreCat | Download (ext.) | arXiv
 
[437]
2023 | Conference Paper | LibreCat-ID: 31880 | OA
Memorization-Dilation: Modeling Neural Collapse Under Noise
D.A. Nguyen, R. Levie, J. Lienen, G. Kutyniok, E. Hüllermeier, in: International Conference on Learning Representations, ICLR, 2023.
LibreCat | Download (ext.)
 
[436]
2023 | Book Chapter | LibreCat-ID: 45884 | OA
Configuration and Evaluation
J.M. Hanselle, E. Hüllermeier, F. Mohr, A.-C. Ngonga Ngomo, M. Sherif, A. Tornede, M.D. Wever, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 85–104.
LibreCat | Files available | DOI
 
[435]
2023 | Book Chapter | LibreCat-ID: 45886 | OA
Composition Analysis in Unknown Contexts
H. Wehrheim, E. Hüllermeier, S. Becker, M. Becker, C. Richter, A. Sharma, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 105–123.
LibreCat | Files available | DOI
 
[434]
2023 | Preprint | LibreCat-ID: 45911 | OA
Mitigating Label Noise through Data Ambiguation
J. Lienen, E. Hüllermeier, ArXiv:2305.13764 (2023).
LibreCat | Download (ext.) | arXiv
 
[433]
2023 | Journal Article | LibreCat-ID: 21600
Efficient time stepping for numerical integration using reinforcement learning
M. Dellnitz, E. Hüllermeier, M. Lücke, S. Ober-Blöbaum, C. Offen, S. Peitz, K. Pfannschmidt, SIAM Journal on Scientific Computing 45 (2023) A579–A595.
LibreCat | Files available | DOI | Download (ext.) | arXiv
 
[432]
2023 | Conference Paper | LibreCat-ID: 51373
Probabilistic Scoring Lists for Interpretable Machine Learning
J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, in: 26th International Conference on Discovery Science , Springer Nature Switzerland, Cham, 2023, pp. 189–203.
LibreCat | DOI
 
[431]
2023 | Book Chapter | LibreCat-ID: 48776
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, Cham, 2023.
LibreCat | DOI
 
[430]
2023 | Book Chapter | LibreCat-ID: 48778
iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios
M. Muschalik, F. Fumagalli, R. Jagtani, B. Hammer, E. Huellermeier, in: Communications in Computer and Information Science, Springer Nature Switzerland, Cham, 2023.
LibreCat | DOI
 
[429]
2023 | Conference Paper | LibreCat-ID: 48775
On Feature Removal for Explainability in Dynamic Environments
F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, in: ESANN 2023 Proceedings, i6doc.com publ., 2023.
LibreCat | DOI
 
[428]
2023 | Conference Paper | LibreCat-ID: 52230
SHAP-IQ: Unified Approximation of any-order Shapley Interactions
F. Fumagalli, M. Muschalik, P. Kolpaczki, E. Hüllermeier, B. Hammer, in: NeurIPS 2023 - Advances in Neural Information Processing Systems, Curran Associates, Inc., 2023, pp. 11515--11551.
LibreCat
 
[427]
2022 | Preprint | LibreCat-ID: 30868
A Survey of Methods for Automated Algorithm Configuration
E. Schede, J. Brandt, A. Tornede, M.D. Wever, V. Bengs, E. Hüllermeier, K. Tierney, ArXiv:2202.01651 (2022).
LibreCat | arXiv
 
[426]
2022 | Conference Paper | LibreCat-ID: 32311
Property-Driven Testing of Black-Box Functions
A. Sharma, V. Melnikov, E. Hüllermeier, H. Wehrheim, in: Proceedings of the 10th IEEE/ACM International Conference on Formal Methods in Software Engineering (FormaliSE), IEEE, 2022, pp. 113–123.
LibreCat
 
[425]
2022 | Conference Paper | LibreCat-ID: 34542
Scikit-Weak: A Python Library for Weakly Supervised Machine Learning
A. Campagner, J. Lienen, E. Hüllermeier, D. Ciucci, in: Lecture Notes in Computer Science, Springer, 2022, pp. 57–70.
LibreCat
 
[424]
2022 | Preprint | LibreCat-ID: 31546 | OA
Conformal Credal Self-Supervised Learning
J. Lienen, C. Demir, E. Hüllermeier, ArXiv:2205.15239 (2022).
LibreCat | Download (ext.)
 
[423]
2022 | Preprint | LibreCat-ID: 30867
Machine Learning for Online Algorithm Selection under Censored Feedback
A. Tornede, V. Bengs, E. Hüllermeier, Proceedings of the 36th AAAI Conference on Artificial Intelligence (2022).
LibreCat | arXiv
 
[422]
2022 | Preprint | LibreCat-ID: 30865
Algorithm Selection on a Meta Level
A. Tornede, L. Gehring, T. Tornede, M.D. Wever, E. Hüllermeier, Machine Learning (2022).
LibreCat | arXiv
 
[421]
2022 | Journal Article | LibreCat-ID: 33090
A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials
K. Gevers, A. Tornede, M.D. Wever, V. Schöppner, E. Hüllermeier, Welding in the World (2022).
LibreCat | DOI
 
[420]
2022 | Report | LibreCat-ID: 36227
Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens
B. Hammer, E. Hüllermeier, V. Lohweg, A. Schneider, W. Schenck, U. Kuhl, M. Braun, A. Pfeifer, C.-A. Holst, M. Schmidt, G. Schomaker, T. Tornede, Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens, 2022.
LibreCat | DOI
 
[419]
2022 | Journal Article | LibreCat-ID: 48780
Agnostic Explanation of Model Change based on Feature Importance
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, KI - Künstliche Intelligenz 36 (2022) 211–224.
LibreCat | DOI
 
[418]
2021 | Journal Article | LibreCat-ID: 24143
Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs!
J.P. Drees, P. Gupta, E. Hüllermeier, T. Jager, A. Konze, C. Priesterjahn, A. Ramaswamy, J. Somorovsky, 14th ACM Workshop on Artificial Intelligence and Security (2021).
LibreCat
 
[417]
2021 | Journal Article | LibreCat-ID: 24148
Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis
A. Ramaswamy, E. Hüllermeier, IEEE Transactions on Artificial Intelligence (to Appear) (2021).
LibreCat
 
[416]
2021 | Journal Article | LibreCat-ID: 21004
AutoML for Multi-Label Classification: Overview and Empirical Evaluation
M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1.
LibreCat | DOI
 
[415]
2021 | Journal Article | LibreCat-ID: 21092
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning
F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (n.d.).
LibreCat
 
[414]
2021 | Conference Paper | LibreCat-ID: 21570
Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance
T. Tornede, A. Tornede, M.D. Wever, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, 2021.
LibreCat
 
[413]
2021 | Journal Article | LibreCat-ID: 21636
Instance weighting through data imprecisiation
J. Lienen, E. Hüllermeier, International Journal of Approximate Reasoning (2021).
LibreCat | Download (ext.)
 
[412]
2021 | Conference Paper | LibreCat-ID: 21637 | OA
From Label Smoothing to Label Relaxation
J. Lienen, E. Hüllermeier, in: Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI, AAAI Press, 2021, pp. 8583–8591.
LibreCat | Download (ext.)
 
[411]
2021 | Conference Paper | LibreCat-ID: 23779
A Meta-Review on Artificial Intelligence in Product Creation
R. Bernijazov, A. Dicks, R. Dumitrescu, M. Foullois, J.M. Hanselle, E. Hüllermeier, G. Karakaya, P. Ködding, V. Lohweg, M. Malatyali, F. Meyer auf der Heide, M. Panzner, C. Soltenborn, in: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 2021.
LibreCat | Download (ext.)
 
[410]
2021 | Conference Paper | LibreCat-ID: 22280
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model
J. Lienen, E. Hüllermeier, R. Ewerth, N. Nommensen, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2021, pp. 14595–14604.
LibreCat
 
[409]
2021 | Preprint | LibreCat-ID: 22509 | OA
Credal Self-Supervised Learning
J. Lienen, E. Hüllermeier, ArXiv:2106.11853 (2021).
LibreCat | Download (ext.)
 
[408]
2021 | Conference Paper | LibreCat-ID: 22913
Automated Machine Learning, Bounded Rationality, and Rational Metareasoning
E. Hüllermeier, F. Mohr, A. Tornede, M.D. Wever, in: 2021.
LibreCat
 
[407]
2021 | Conference Paper | LibreCat-ID: 27381
Ranking Structured Objects with Graph Neural Networks
C. Damke, E. Hüllermeier, in: C. Soares, L. Torgo (Eds.), Proceedings of The 24th International Conference on Discovery Science (DS 2021), Springer, 2021, pp. 166–180.
LibreCat | DOI | arXiv
 
[406]
2021 | Preprint | LibreCat-ID: 30866
Towards Green Automated Machine Learning: Status Quo and Future Directions
T. Tornede, A. Tornede, J.M. Hanselle, M.D. Wever, F. Mohr, E. Hüllermeier, ArXiv:2111.05850 (2021).
LibreCat | arXiv
 
[405]
2021 | Conference Paper | LibreCat-ID: 21198 LibreCat
 
[404]
2021 | Book Chapter | LibreCat-ID: 29292 | OA
Drift Detection in Text Data with Document Embeddings
R. Feldhans, A. Wilke, S. Heindorf, M.H. Shaker, B. Hammer, A.-C. Ngonga Ngomo, E. Hüllermeier, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer International Publishing, Cham, 2021.
LibreCat | Files available | DOI | Download (ext.)
 
[403]
2021 | Working Paper | LibreCat-ID: 45616
Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes
D. van Straaten, V. Melnikov, E. Hüllermeier, B. Mir Djawadi, R. Fahr, Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes, 2021.
LibreCat
 
[402]
2021 | Journal Article | LibreCat-ID: 24456 | OA
Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems
K.J. Rohlfing, P. Cimiano, I. Scharlau, T. Matzner, H.M. Buhl, H. Buschmeier, E. Esposito, A. Grimminger, B. Hammer, R. Haeb-Umbach, I. Horwath, E. Hüllermeier, F. Kern, S. Kopp, K. Thommes, A.-C. Ngonga Ngomo, C. Schulte, H. Wachsmuth, P. Wagner, B. Wrede, IEEE Transactions on Cognitive and Developmental Systems 13 (2021) 717–728.
LibreCat | Files available | DOI
 
[401]
2020 | Preprint | LibreCat-ID: 19603 | OA
Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control
H. Bode, S.H. Heid, D. Weber, E. Hüllermeier, O. Wallscheid, ArXiv:2005.04869 (2020).
LibreCat | Download (ext.)
 
[400]
2020 | Conference Paper | LibreCat-ID: 19953 | OA
A Novel Higher-order Weisfeiler-Lehman Graph Convolution
C. Damke, V. Melnikov, E. Hüllermeier, in: S. Jialin Pan, M. Sugiyama (Eds.), Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020), PMLR, Bangkok, Thailand, 2020, pp. 49–64.
LibreCat | Files available | arXiv
 
[399]
2020 | Preprint | LibreCat-ID: 20211 | OA
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model
J. Lienen, E. Hüllermeier, ArXiv:2010.13118 (2020).
LibreCat | Download (ext.)
 
[398]
2020 | Conference Paper | LibreCat-ID: 24146
Constrained Multi-Agent Optimization with Unbounded Information Delay
S.H. Heid, A. Ramaswamy, E. Hüllermeier, in: Proceedings-30. Workshop Computational Intelligence: Berlin, 26.-27. November 2020, 2020, p. 247.
LibreCat
 
[397]
2020 | Conference Paper | LibreCat-ID: 17407
Extreme Algorithm Selection with Dyadic Feature Representation
A. Tornede, M.D. Wever, E. Hüllermeier, in: Discovery Science, 2020.
LibreCat
 
[396]
2020 | Conference Paper | LibreCat-ID: 17408
Hybrid Ranking and Regression for Algorithm Selection
J.M. Hanselle, A. Tornede, M.D. Wever, E. Hüllermeier, in: KI 2020: Advances in Artificial Intelligence, 2020.
LibreCat
 
[395]
2020 | Conference Paper | LibreCat-ID: 17424
AutoML for Predictive Maintenance: One Tool to RUL Them All
T. Tornede, A. Tornede, M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the ECMLPKDD 2020, 2020.
LibreCat | DOI
 
[394]
2020 | Preprint | LibreCat-ID: 17605 | OA
Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction
S.H. Heid, M.D. Wever, E. Hüllermeier, Journal of Data Mining and Digital Humanities (n.d.).
LibreCat | Download (ext.)
 
[393]
2020 | Conference Paper | LibreCat-ID: 20306
Towards Meta-Algorithm Selection
A. Tornede, M.D. Wever, E. Hüllermeier, in: Workshop MetaLearn 2020 @ NeurIPS 2020, 2020.
LibreCat
 
[392]
2020 | Book Chapter | LibreCat-ID: 18014
Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach
A. El Mesaoudi-Paul, D. Weiß, V. Bengs, E. Hüllermeier, K. Tierney, in: Learning and Intelligent Optimization. LION 2020., Springer, Cham, 2020, pp. 216–232.
LibreCat | DOI
 
[391]
2020 | Preprint | LibreCat-ID: 18017
Online Preselection with Context Information under the Plackett-Luce Model
A. El Mesaoudi-Paul, V. Bengs, E. Hüllermeier, ArXiv:2002.04275 (n.d.).
LibreCat
 
[390]
2020 | Conference Paper | LibreCat-ID: 18276
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis
A. Tornede, M.D. Wever, S. Werner, F. Mohr, E. Hüllermeier, in: ACML 2020, 2020.
LibreCat | Download (ext.)
 
[389]
2020 | Journal Article | LibreCat-ID: 16725
Algorithm Selection for Software Validation Based on Graph Kernels
C. Richter, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, Journal of Automated Software Engineering (n.d.).
LibreCat
 
[388]
2020 | Conference Paper | LibreCat-ID: 15629
LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification
M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, in: Springer, n.d.
LibreCat
 
[387]
2019 | Conference Abstract | LibreCat-ID: 8868
Towards Automated Machine Learning for Multi-Label Classification
M.D. Wever, F. Mohr, E. Hüllermeier, A. Hetzer, in: 2019.
LibreCat | Files available
 
[386]
2019 | Journal Article | LibreCat-ID: 10578
Choice Functions Generated by Mallows and Plackett–Luce Relations
V.K. Tagne, S. Fotso, L.A. Fono, E. Hüllermeier, New Mathematics and Natural Computation 15 (2019) 191–213.
LibreCat
 
[385]
2019 | Journal Article | LibreCat-ID: 15001
Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning
I. Couso, C. Borgelt, E. Hüllermeier, R. Kruse, IEEE Computational Intelligence Magazine (2019) 31–44.
LibreCat | DOI
 
[384]
2019 | Journal Article | LibreCat-ID: 15002 | OA
Multi-target prediction: a unifying view on problems and methods
W. Waegeman, K. Dembczynski, E. Hüllermeier, Data Mining and Knowledge Discovery 33 (2019) 293–324.
LibreCat | Files available | DOI
 
[383]
2019 | Conference Paper | LibreCat-ID: 15003
Set-Valued Prediction in Multi-Class Classification
T. Mortier, M. Wydmuch, K. Dembczynski, E. Hüllermeier, W. Waegeman, in: Proceedings of the 31st Benelux Conference on Artificial Intelligence {(BNAIC} 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019, 2019.
LibreCat
 
[382]
2019 | Book Chapter | LibreCat-ID: 15004
Feature Selection for Analogy-Based Learning to Rank
M. Ahmadi Fahandar, E. Hüllermeier, in: Discovery Science, Cham, 2019.
LibreCat | DOI
 
[381]
2019 | Book Chapter | LibreCat-ID: 15005
Analogy-Based Preference Learning with Kernels
M. Ahmadi Fahandar, E. Hüllermeier, in: KI 2019: Advances in Artificial Intelligence, Cham, 2019.
LibreCat | DOI
 
[380]
2019 | Book Chapter | LibreCat-ID: 15006
Epistemic Uncertainty Sampling
V.-L. Nguyen, S. Destercke, E. Hüllermeier, in: Discovery Science, Cham, 2019.
LibreCat | DOI
 
[379]
2019 | Conference Paper | LibreCat-ID: 15007 | OA
Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA
V. Melnikov, E. Hüllermeier, in: Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101), 2019.
LibreCat | Files available | DOI
 
[378]
2019 | Conference Paper | LibreCat-ID: 15011 | OA
Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking
A. Tornede, M.D. Wever, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, KIT Scientific Publishing, Karlsruhe, 2019, pp. 135–146.
LibreCat | Files available
 
[377]
2019 | Conference Paper | LibreCat-ID: 15013
A Reduction of Label Ranking to Multiclass Classification
K. Brinker, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Würzburg, Germany, 2019.
LibreCat
 
[376]
2019 | Conference Paper | LibreCat-ID: 15014
Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants
E. Hüllermeier, I. Couso, S. Diestercke, in: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.
LibreCat
 
[375]
2019 | Journal Article | LibreCat-ID: 15015
Mining Rank Data
S. Henzgen, E. Hüllermeier, ACM Transactions on Knowledge Discovery from Data (2019) 1–36.
LibreCat | DOI
 
[374]
2019 | Conference Abstract | LibreCat-ID: 13132
From Automated to On-The-Fly Machine Learning
F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, in: INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft, Gesellschaft für Informatik e.V., Bonn, 2019, pp. 273–274.
LibreCat
 
[373]
2019 | Conference Paper | LibreCat-ID: 10232 | OA
Automating Multi-Label Classification Extending ML-Plan
M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.
LibreCat | Files available
 
[372]
2019 | Journal Article | LibreCat-ID: 20243
Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches
K. Rohlfing, G. Leonardi, I. Nomikou, J. Rączaszek-Leonardi, E. Hüllermeier, IEEE Transactions on Cognitive and Developmental Systems (2019).
LibreCat | DOI
 
[371]
2018 | Conference Paper | LibreCat-ID: 2479 | OA
(WIP) Towards the Automated Composition of Machine Learning Services
F. Mohr, M.D. Wever, E. Hüllermeier, A. Faez, in: SCC, IEEE, San Francisco, CA, USA, 2018.
LibreCat | Files available | DOI | Download (ext.)
 
[370]
2018 | Conference Paper | LibreCat-ID: 2857 | OA
Programmatic Task Network Planning
F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39.
LibreCat | Files available | Download (ext.)
 
[369]
2018 | Conference Paper | LibreCat-ID: 2471 | OA
On-The-Fly Service Construction with Prototypes
F. Mohr, M.D. Wever, E. Hüllermeier, in: SCC, IEEE Computer Society, San Francisco, CA, USA, 2018.
LibreCat | Files available | DOI | Download (ext.)
 
[368]
2018 | Journal Article | LibreCat-ID: 3402 LibreCat | Files available | DOI
 
[367]
2018 | Journal Article | LibreCat-ID: 3510 | OA
ML-Plan: Automated Machine Learning via Hierarchical Planning
F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning (2018) 1495–1515.
LibreCat | Files available | DOI | Download (ext.)
 
[366]
2018 | Conference Paper | LibreCat-ID: 3552 | OA
Reduction Stumps for Multi-Class Classification
F. Mohr, M.D. Wever, E. Hüllermeier, in: Proceedings of the Symposium on Intelligent Data Analysis, ‘s-Hertogenbosch, the Netherlands, n.d.
LibreCat | Files available | DOI | Download (ext.)
 
[365]
2018 | Conference Paper | LibreCat-ID: 3852 | OA
ML-Plan for Unlimited-Length Machine Learning Pipelines
M.D. Wever, F. Mohr, E. Hüllermeier, in: ICML 2018 AutoML Workshop, 2018.
LibreCat | Files available | Download (ext.)
 
[364]
2018 | Conference Paper | LibreCat-ID: 2109 | OA
Ensembles of Evolved Nested Dichotomies for Classification
M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, Kyoto, Japan, 2018.
LibreCat | Files available | DOI | Download (ext.)
 
[363]
2018 | Preprint | LibreCat-ID: 17713 | OA
Automated Multi-Label Classification based on ML-Plan
M.D. Wever, F. Mohr, E. Hüllermeier, (2018).
LibreCat | Download (ext.)
 
[362]
2018 | Preprint | LibreCat-ID: 17714 | OA
Automated machine learning service composition
F. Mohr, M.D. Wever, E. Hüllermeier, (2018).
LibreCat | Download (ext.)
 
[361]
2018 | Book Chapter | LibreCat-ID: 6423
Preference-Based Reinforcement Learning Using Dyad Ranking
D. Schäfer, E. Hüllermeier, in: Discovery Science, Springer International Publishing, Cham, 2018, pp. 161–175.
LibreCat | Files available | DOI
 
[360]
2018 | Conference (Editor) | LibreCat-ID: 10591
Research Directions for Principles of Data Management
S. Abiteboul, M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David, R. Hull, E. Hüllermeier, B. Kimelfeld, L. Libkin, W. Martens, T. Milo, F. Murlak, F. Neven, M. Ortiz, T. Schwentick, J. Stoyanovich, J. Su, D. Suciu, V. Vianu, K. Yi, eds., Research Directions for Principles of Data Management, 2018.
LibreCat
 
[359]
2018 | Book Chapter | LibreCat-ID: 10783
Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators
I. Couso, E. Hüllermeier, in: S. Mostaghim, A. Nürnberger, C. Borgelt (Eds.), Frontiers in Computational Intelligence, Springer, 2018, pp. 31–46.
LibreCat
 
[358]
2018 | Journal Article | LibreCat-ID: 16038
Dyad ranking using Plackett-Luce models based on joint feature representations
D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941.
LibreCat
 
[357]
2018 | Conference Paper | LibreCat-ID: 10145
Learning to Rank Based on Analogical Reasoning
M. Ahmadi Fahandar, E. Hüllermeier, in: Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2018, pp. 2951–2958.
LibreCat
 
[356]
2018 | Conference Paper | LibreCat-ID: 10148
Ranking Distributions based on Noisy Sorting
A. El Mesaoudi-Paul, E. Hüllermeier, R. Busa-Fekete, in: Proc. 35th Int. Conference on Machine Learning (ICML), Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018, pp. 3469–3477.
LibreCat
 
[355]
2018 | Conference Paper | LibreCat-ID: 10149
A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart
M. Hesse, J. Timmermann, E. Hüllermeier, A. Trächtler, in: Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 2018, pp. 15–20.
LibreCat
 
[354]
2018 | Book Chapter | LibreCat-ID: 10152
Learning interpretable rules for multi-label classification
E.L. Mencia, J. Fürnkranz, E. Hüllermeier, M. Rapp, in: H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, M.A.J. van Gerven (Eds.), Explainable and Interpretable Models in Computer Vision and Machine Learning, Springer, 2018, pp. 81–113.
LibreCat
 
[353]
2018 | Conference Paper | LibreCat-ID: 10181
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty
V.-L. Nguyen, S. Destercke, M.-H. Masson, E. Hüllermeier, in: Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095.
LibreCat
 
[352]
2018 | Conference Paper | LibreCat-ID: 10184
Preference-Based Reinforcement Learning Using Dyad Ranking
D. Schäfer, E. Hüllermeier, in: Proc. 21st Int. Conference on Discovery Science (DS), 2018, pp. 161–175.
LibreCat
 
[351]
2018 | Journal Article | LibreCat-ID: 10276
Dyad Ranking Using Plackett-Luce Models based on joint feature representations
D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941.
LibreCat
 
[350]
2018 | Conference Abstract | LibreCat-ID: 1379 | OA
Supporting the Cognitive Process in Annotation Tasks
N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M.D. Wever, E. Hüllermeier, in: K. Eckart, D. Schlechtweg (Eds.), Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, 2018.
LibreCat | Files available | Download (ext.)
 
[349]
2018 | Journal Article | LibreCat-ID: 22996
A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart
M. Hesse, J. Timmermann, E. Hüllermeier, A. Trächtler, Procedia Manufacturing 24 (2018) 15–20.
LibreCat
 
[348]
2017 | Conference Paper | LibreCat-ID: 3325
Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics
V. Melnikov, E. Hüllermeier, in: Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing, 2017.
LibreCat | Files available | DOI
 
[347]
2017 | Conference Paper | LibreCat-ID: 71
Predicting Rankings of Software Verification Tools
M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proceedings of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26.
LibreCat | Files available | DOI
 
[346]
2017 | Report | LibreCat-ID: 72
Predicting Rankings of Software Verification Competitions
M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, Predicting Rankings of Software Verification Competitions, 2017.
LibreCat | Files available
 
[345]
2017 | Encyclopedia Article | LibreCat-ID: 10589
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: Encyclopedia of Machine Learning and Data Mining, 2017, pp. 1000–1005.
LibreCat
 
[344]
2017 | Book Chapter | LibreCat-ID: 10784
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2017, pp. 1000–1005.
LibreCat
 
[343]
2017 | Conference Paper | LibreCat-ID: 1180 | OA
Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization
M.D. Wever, F. Mohr, E. Hüllermeier, in: 27th Workshop Computational Intelligence, Dortmund, 2017.
LibreCat | Files available | Download (ext.)
 
[342]
2017 | Conference Paper | LibreCat-ID: 15397
Optimizing the structure of nested dichotomies. A comparison of two heuristics
V. Melnikov, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, KIT Scientific Publishing, 2017, pp. 1–12.
LibreCat
 
[341]
2017 | Conference Paper | LibreCat-ID: 15399
Predicting rankings of software verification tools
M. Czech, E. Hüllermeier, M.C. Jacobs, H. Wehrheim, in: In Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany, 2017.
LibreCat
 
[340]
2017 | Conference Paper | LibreCat-ID: 15110
Maximum likelihood estimation and coarse data
I. Couso, D. Dubois, E. Hüllermeier, in: In Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain, Springer, 2017, pp. 3–16.
LibreCat
 
[339]
2017 | Conference Paper | LibreCat-ID: 10204
Estimating relative depth in single images via rankboost
R. Ewerth, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok, K. Dembczynski, E. Hüllermeier, in: Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 2017, pp. 919–924.
LibreCat
 
[338]
2017 | Conference Paper | LibreCat-ID: 10205
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
M. Ahmadi Fahandar, E. Hüllermeier, I. Couso, in: Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 2017, pp. 1078–1087.
LibreCat
 
[337]
2017 | Conference Paper | LibreCat-ID: 10206 | OA
Planning with Independent Task Networks
F. Mohr, T. Lettmann, E. Hüllermeier, in: Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017), 2017, pp. 193–206.
LibreCat | Files available | DOI
 
[336]
2017 | Conference Paper | LibreCat-ID: 10207
Predicting rankings of software verification tools
M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 2017, pp. 23–26.
LibreCat
 
[335]
2017 | Conference Paper | LibreCat-ID: 10208
Maximum Likelihood Estimation and Coarse Data
I. Couso, D. Dubois, E. Hüllermeier, in: Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 2017, pp. 3–16.
LibreCat
 
[334]
2017 | Conference Paper | LibreCat-ID: 10209
Learning to Rank based on Analogical Reasoning
M. Ahmadi Fahandar, E. Hüllermeier, in: Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence, 2017.
LibreCat
 
[333]
2017 | Conference Paper | LibreCat-ID: 10212 LibreCat
 
[332]
2017 | Conference Paper | LibreCat-ID: 10213
Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics
V. Melnikov, E. Hüllermeier, in: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.
LibreCat
 
[331]
2017 | Conference Paper | LibreCat-ID: 10216
Learning TSK Fuzzy Rules from Data Streams
A. Shaker, W. Heldt, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.
LibreCat
 
[330]
2017 | Journal Article | LibreCat-ID: 10267
Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting
M. Bräuning, E. Hüllermeier, T. Keller, M. Glaum, European Journal of Operational Research 258 (2017) 295–306.
LibreCat
 
[329]
2017 | Journal Article | LibreCat-ID: 10268
Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic
M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions on Software Engineering 43 (2017) 739–759.
LibreCat
 
[328]
2017 | Journal Article | LibreCat-ID: 10269
From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection
E. Hüllermeier, The Computing Research Repository  (CoRR) (2017).
LibreCat
 
[327]
2016 | Journal Article | LibreCat-ID: 3318
Pairwise versus Pointwise Ranking: A Case Study
V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, Pritha Gupta, Schedae Informaticae 25 (2016).
LibreCat | Files available | DOI
 
[326]
2016 | Journal Article | LibreCat-ID: 190
Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic
M.C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017 (2016) 739–759.
LibreCat | Files available | DOI
 
[325]
2016 | Conference Paper | LibreCat-ID: 184
Learning to Aggregate Using Uninorms
V. Melnikov, E. Hüllermeier, in: Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771.
LibreCat | Files available | DOI
 
[324]
2016 | Encyclopedia Article | LibreCat-ID: 10785
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2016.
LibreCat
 
[323]
2016 | Conference Paper | LibreCat-ID: 15400
On the identifiability of models in multi-criteria preference learning
C. Labreuche, E. Hüllermeier, P. Vojtas, A. Fallah Tehrani, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.
LibreCat
 
[322]
2016 | Conference Paper | LibreCat-ID: 15401
Preference -based reinforcement learning using dyad ranking
D. Schäfer, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany, 2016.
LibreCat
 
[321]
2016 | Conference Paper | LibreCat-ID: 15402
Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators
I. Couso, M. Ahmadi Fahandar, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.
LibreCat
 
[320]
2016 | Conference Paper | LibreCat-ID: 15403
Support vector classification on noisy data using fuzzy superset losses
S. Lu, E. Hüllermeier, in: E. Hüllermeier, F. Hoffmann, R. Mikut (Eds.), In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, KIT Scientific Publishing, 2016, pp. 1–8.
LibreCat
 
[319]
2016 | Conference Paper | LibreCat-ID: 15404
Plackett-Luce networks for dyad ranking
D. Schäfer, E. Hüllermeier, in: In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016.
LibreCat
 
[318]
2016 | Conference Paper | LibreCat-ID: 15111
Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical concepts
K. Pfannschmidt, E. Hüllermeier, S. Held, R. Neiger, in: In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–461.
LibreCat
 
[317]
2016 | Journal Article | LibreCat-ID: 16041
CavSimBase: A database for large scale comparison of protein binding sites
M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, E. Hüllermeier, IEEE Transactions on Knowledge and Data Engineering 28 (2016) 1423–1434.
LibreCat
 
[316]
2016 | Book Chapter | LibreCat-ID: 10214
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2016.
LibreCat
 
[315]
2016 | Conference (Editor) | LibreCat-ID: 10221
Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany
F. Hoffmann, E. Hüllermeier, R. Mikut, eds., Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany, 2016.
LibreCat
 
[314]
2016 | Conference Paper | LibreCat-ID: 10222
Extreme F-measure maximization using sparse probability estimates
K. Jasinska, K. Dembczynski, R. Busa-Fekete, T. Klerx, E. Hüllermeier, in: M.F. Balcan, K.Q. Weinberger (Eds.), Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA, 2016.
LibreCat
 
[313]
2016 | Conference Paper | LibreCat-ID: 10223
Learning to aggregate using uninorms, in Proceedings ECML/PKDD-2016
V. Melnikov, E. Hüllermeier, in: European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 756–771.
LibreCat
 
[312]
2016 | Conference Paper | LibreCat-ID: 10224
Consistency of probalistic classifier trees
K. Dembczynski, W. Kotlowski, W. Waegeman, R. Busa-Fekete, E. Hüllermeier, in: In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 511–526.
LibreCat
 
[311]
2016 | Conference Paper | LibreCat-ID: 10225
Predicting the electricity consumption of buildings: An improved CBR approach
A. Shabani, A. Paul, R. Platon, E. Hüllermeier, in: In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 2016, pp. 356–369.
LibreCat
 
[310]
2016 | Conference Paper | LibreCat-ID: 10226
Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical concepts
K. Pfannschmidt, E. Hüllermeier, S. Held, R. Neiger, in: In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–461.
LibreCat
 
[309]
2016 | Conference Paper | LibreCat-ID: 10227
On the Identifiability of models in multi-criteria preference learning
C. Labreuche, E. Hüllermeier, P. Vojtas, A. Fallah Tehrani, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.
LibreCat
 
[308]
2016 | Conference Paper | LibreCat-ID: 10228
Preference-Based Reinforcement Learning Using Dyad Ranking
D. Schäfer, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.
LibreCat
 
[307]
2016 | Conference Paper | LibreCat-ID: 10229
Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators
I. Couso, M. Ahmadi Fahandar, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.
LibreCat
 
[306]
2016 | Conference Paper | LibreCat-ID: 10230
Support vector classification on noisy data using fuzzy supersets losses
S. Lu, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing, 2016, pp. 1–8.
LibreCat
 
[305]
2016 | Conference Paper | LibreCat-ID: 10231
Plackett-Luce networks for dyad ranking
D. Schäfer, E. Hüllermeier, in: In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016.
LibreCat
 
[304]
2016 | Conference (Editor) | LibreCat-ID: 10263
ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial Intelligence
G.A. Kaminka, M. Fox, P. Bouquet, E. Hüllermeier, V. Dignum, F. Dignum, F. van Harmelen, eds., ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence, IOS Press, The Hague, The Netherlands, 2016.
LibreCat
 
[303]
2016 | Journal Article | LibreCat-ID: 10264
CavSimBase: A database for large scale comparison of protein binding sites
M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, E. Hüllermeier, IEEE Transactions on Knowledge and Data Engineering 28 (2016) 1423–1434.
LibreCat
 
[302]
2016 | Journal Article | LibreCat-ID: 10266 LibreCat
 
[301]
2015 | Journal Article | LibreCat-ID: 4792
Fast Fuzzy Pattern Tree Learning for Classification
R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.
LibreCat | Files available | DOI
 
[300]
2015 | Conference Paper | LibreCat-ID: 15406
Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations
D. Schäfer, E. Hüllermeier, in: In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located ECML/PKDD, Porto, Portugal, 2015, pp. 110–111.
LibreCat
 
[299]
2015 | Conference Paper | LibreCat-ID: 15749
A cbr approach to the angry birds game
A. Paul, E. Hüllermeier, in: In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany, 2015, pp. 68–77.
LibreCat
 
[298]
2015 | Conference Paper | LibreCat-ID: 15750
Depth estimation in monocular images: Quantitative versus qualitative approaches
R. Ewerth, A. Balz, J. Gehlhaar, K. Dembczynski, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier (Eds.), In Proceedings 25. Workshop Computational Intelligence, Dortmund, Germany, KIT Scientific Publishing, 2015, pp. 235–240.
LibreCat
 
[297]
2015 | Conference Paper | LibreCat-ID: 15751
Locally weighted regression through data imprecisiation
S. Lu, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier (Eds.), In Proceedings 25th Workshop Computational Intelligence, Dortmund Germany, KIT Scientific Publishing, 2015, pp. 97–104.
LibreCat
 
[296]
2015 | Journal Article | LibreCat-ID: 16049
Fast fuzzy pattern tree learning for classification
R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.
LibreCat
 
[295]
2015 | Journal Article | LibreCat-ID: 16051 LibreCat
 
[294]
2015 | Journal Article | LibreCat-ID: 16053
Does machine learning need fuzzy logic?
E. Hüllermeier, Fuzzy Sets and Systems 281 (2015) 292–299.
LibreCat
 
[293]
2015 | Journal Article | LibreCat-ID: 16058
On the Bayes-optimality of F-measure maximizers
W. Waegeman, K. Dembczynski, A. Jachnik, W. Cheng, E. Hüllermeier, Journal of Machine Learning Research 15 (2015) 3313–3368.
LibreCat
 
[292]
2015 | Journal Article | LibreCat-ID: 16067 LibreCat
 
[291]
2015 | Conference Paper | LibreCat-ID: 10234
Case-Based Reasoning Research and Development
E. Hüllermeier, M. Minor, in: In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015) LNAI 9343, Springer, 2015.
LibreCat
 
[290]
2015 | Conference Paper | LibreCat-ID: 10235 LibreCat
 
[289]
2015 | Conference Paper | LibreCat-ID: 10236
Case Base Maintenance in Preference-Based CBR
A. Abdel-Aziz, E. Hüllermeier, in: In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 1–14.
LibreCat
 
[288]
2015 | Conference Paper | LibreCat-ID: 10237
Qualitative Multi-Armed Bandits: A Quantile-Based Approach
B. Szörényi, R. Busa-Fekete, P. Weng, E. Hüllermeier, in: In Proceedings International Conference on Machine Learning (ICML 2015), 2015, pp. 1660–1668.
LibreCat
 
[287]
2015 | Conference Paper | LibreCat-ID: 10238
Dyad Ranking Using A Bilinear Plackett-Luce Model
D. Schäfer, E. Hüllermeier, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 227–242.
LibreCat
 
[286]
2015 | Conference Paper | LibreCat-ID: 10239
Superset Learning Based on Generalized Loss Minimization
E. Hüllermeier, W. Cheng, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 260–275.
LibreCat
 
[285]
2015 | Conference Paper | LibreCat-ID: 10240
Weighted Rank Correlation : A Flexible Approach Based on Fuzzy Order Relations
S. Henzgen, E. Hüllermeier, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 422–437.
LibreCat
 
[284]
2015 | Conference Paper | LibreCat-ID: 10241
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach
B. Szörényi, R. Busa-Fekete, A. Paul, E. Hüllermeier, in: In Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 604–612.
LibreCat
 
[283]
2015 | Conference Paper | LibreCat-ID: 10242
Online F-Measure Optimization
B. Szörényi, R. Busa-Fekete, K. Dembczynski, E. Hüllermeier, in: In Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 595–603.
LibreCat
 
[282]
2015 | Conference Paper | LibreCat-ID: 10243
A CBR Approach to the Angry Birds Game
A. El Mesaoudi-Paul, E. Hüllermeier, in: In Workshop Proc. 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 68–77.
LibreCat
 
[281]
2015 | Conference Paper | LibreCat-ID: 10244
Preference-Based Meta- Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations
D. Schäfer, E. Hüllermeier, in: In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel@PKDD/ECML), 2015, pp. 110–111.
LibreCat
 
[280]
2015 | Conference Paper | LibreCat-ID: 10245
Locally weighted regression through data imprecisiation
S. Lu, E. Hüllermeier, in: Proceedings 25. Workshop Computational Intelligence, 2015, pp. 97–104.
LibreCat
 
[279]
2015 | Conference Paper | LibreCat-ID: 10246
Depth estimation in monocular images: Quantitative versus qualitative approaches
R. Ewerth, A. Balz, J. Gehlhaar, K. Dembczynski, E. Hüllermeier, in: Proceedings 25. Workshop Computational Intelligence, 2015, pp. 235–240.
LibreCat
 
[278]
2015 | Journal Article | LibreCat-ID: 10319
On the Bayes-Optimality of F-Measure Maximizers
W. Waegeman, K. Dembczynski, A. Jachnik, W. Cheng, E. Hüllermeier, In Journal of Machine Learning Research 15 (2015) 3333–3388.
LibreCat
 
[277]
2015 | Journal Article | LibreCat-ID: 10320
Does machine learning need fuzzy logic?
E. Hüllermeier, Fuzzy Sets and Systems 281 (2015) 292–299.
LibreCat
 
[276]
2015 | Journal Article | LibreCat-ID: 10321 LibreCat
 
[275]
2015 | Journal Article | LibreCat-ID: 10322 LibreCat
 
[274]
2015 | Journal Article | LibreCat-ID: 10323
Overlap Indices: Construction of and Application of Interpolative Fuzzy Systems
S. Garcia-Jimenez, U. Bustince, E. Hüllermeier, R. Mesiar, N.R. Pal, A. Pradera, IEEE Transactions on Fuzzy Systems 23 (2015) 1259–1273.
LibreCat
 
[273]
2015 | Journal Article | LibreCat-ID: 10324
Fast Fuzzy Pattern Tree Learning of Classification
R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.
LibreCat
 
[272]
2014 | Journal Article | LibreCat-ID: 16046
Preference-based learning of ideal solutions in TOPSIS-like decision models
M. Agarwal, A. Fallah Tehrani, E. Hüllermeier, Journal of Multi-Criteria Decision Analysis 22 (2014).
LibreCat
 
[271]
2014 | Journal Article | LibreCat-ID: 16060
Extended graph-based models for enhanced similarity search in Cabase
T. Krotzky, T. Fober, E. Hüllermeier, G. Klebe, IEEE/ACM Transactions of Computational Biology and Bioinformatics 11 (2014) 878–890.
LibreCat
 
[270]
2014 | Journal Article | LibreCat-ID: 16064
Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization
E. Hüllermeier, International Journal of Approximate Reasoning 55 (2014) 1519–1534.
LibreCat
 
[269]
2014 | Journal Article | LibreCat-ID: 16069
Visualization of evolving fuzzy-rule-based systems
S. Henzgen, M. Strickert, E. Hüllermeier, Evolving Systems 5 (2014) 175–191.
LibreCat
 
[268]
2014 | Journal Article | LibreCat-ID: 16077
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm.
R. Busa-Fekete, B. Szörenyi, P. Weng, W. Cheng, E. Hüllermeier, Machine Learning 97 (2014) 327–351.
LibreCat
 
[267]
2014 | Journal Article | LibreCat-ID: 16078
Open challenges for data stream mining research
G. Krempl, I. Zliobaite, D. Brzezinski, E. Hüllermeier, M. Last, V. Lemaire, T. Noack, A. Shaker, S. Sievi, M. Spiliopoulou, J. Stefanowski, SIGKDD Explorations 16 (2014) 1–10.
LibreCat
 
[266]
2014 | Journal Article | LibreCat-ID: 16079
Correlation-based embedding of pairwise score data
M. Strickert, K. Bunte, F.M. Schleif, E. Hüllermeier, Neurocomputing 141 (2014) 97–109.
LibreCat
 
[265]
2014 | Journal Article | LibreCat-ID: 16080
Survival analysis on data streams: Analyzing temporal events in dynamically changing environments
A. Shaker, E. Hüllermeier, International Journal of Applied Mathematics and Computer Science 24 (2014) 199–212.
LibreCat
 
[264]
2014 | Journal Article | LibreCat-ID: 16082
Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty
R. Senge, S. Bösner, K. Dembczynski, J. Haasenritter, O. Hirsch, N. Donner-Banzhoff, E. Hüllermeier, Information Sciences 255 (2014) 16–29.
LibreCat
 
[263]
2014 | Journal Article | LibreCat-ID: 16083
The comprehensive diagnostic study is suggested as a design to model the diagnostic process
N. Donner-Banzhoff, J. Haasenritter, E. Hüllermeier, A. Viniol, S. Bösner, A. Becker, Journal of Clinical Epidemiology 2 (2014) 124–132.
LibreCat
 
[262]
2014 | Conference Paper | LibreCat-ID: 10247
PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences
R. Busa-Fekete, B. Szörényi, E. Hüllermeier, in: Proceedings AAAI 2014, Quebec, Canada, 2014, pp. 1701–1707.
LibreCat
 
[261]
2014 | Conference Paper | LibreCat-ID: 10248
A Survey of Preference-Based Online Learning with Bandit Algorithms
R. Busa-Fekete, E. Hüllermeier, in: Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia, 2014, pp. 18–39.
LibreCat
 
[260]
2014 | Conference Paper | LibreCat-ID: 10249
Mining Rank Data
S. Henzgen, E. Hüllermeier, in: Proceedings Discovery Science, Bled,Slovenia , 2014, pp. 123–134.
LibreCat
 
[259]
2014 | Conference Paper | LibreCat-ID: 10250
The Choquet kernel for monotone data
A. Fallah Tehrani, M. Strickert, E. Hüllermeier, in: Proceedings ESANN , Bruges, Belgium, 2014.
LibreCat
 
[258]
2014 | Conference Paper | LibreCat-ID: 10251
Learning Solution Similarity in Preference-Based CBR
A. Abdel-Aziz, M. Strickert, E. Hüllermeier, in: Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland, 2014, pp. 17–31.
LibreCat
 
[257]
2014 | Conference Paper | LibreCat-ID: 10253
Dyad Ranking Using A Bilinear Plackett-Luce Model
D. Schäfer, E. Hüllermeier, in: Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany, 2014, pp. 32–33.
LibreCat
 
[256]
2014 | Conference Paper | LibreCat-ID: 10254
Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France
T. Calders, F. Esposito, E. Hüllermeier, R. Meo, in: Proceedings, Parts I-III. Lecture Notes in Computer Science, Springer, 2014, pp. 8724–8726.
LibreCat
 
[255]
2014 | Conference Paper | LibreCat-ID: 10295
Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports
J. Fürnkranz, E. Hüllermeier, C. Rudin, R. Slowinski, S. Sanner, in: 2014, pp. 1–27.
LibreCat
 
[254]
2014 | Journal Article | LibreCat-ID: 10296
Survival analysis on data streams: Analyzing temporal events in dynamically changing environments
A. Shaker, E. Hüllermeier, Applied Mathematics and Computer Science 24 (2014) 199–212.
LibreCat
 
[253]
2014 | Journal Article | LibreCat-ID: 10297
Ausgewählte Beiträge des GMA-Fachausschusses 5.14
F. Hoffmann, E. Hüllermeier, A. Kroll, Computational Intelligence Automatisierungstechnik 62 (2014) 685–686.
LibreCat
 
[252]
2014 | Journal Article | LibreCat-ID: 10298
Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track
T. Calders, F. Esposito, E. Hüllermeier, R. Meo, Data Min. Knowledge Discovery 28 (2014) 1129–1133.
LibreCat
 
[251]
2014 | Journal Article | LibreCat-ID: 10299
Visualization of evolving fuzzy rule-based systems
S. Henzgen, M. Strickert, E. Hüllermeier, Evolving Systems 5 (2014) 175–191.
LibreCat
 
[250]
2014 | Journal Article | LibreCat-ID: 10308 LibreCat
 
[249]
2014 | Journal Article | LibreCat-ID: 10309 LibreCat
 
[248]
2014 | Journal Article | LibreCat-ID: 10310
Correlation-based embedding of pairwise score data
M. Strickert, K. Bunte, F.-M. Schleif, E. Hüllermeier, Neurocomputing 141 (2014) 97–109.
LibreCat
 
[247]
2014 | Journal Article | LibreCat-ID: 10311
Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty
R. Senge, S. Bösner, K. Dembczynski, J. Haasenritter, O. Hirsch, N. Donner-Banzhoff, E. Hüllermeier, Information Sciences 255 (2014) 16–29.
LibreCat
 
[246]
2014 | Journal Article | LibreCat-ID: 10312
Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances
M. Mernberger, M. Moog, S. Stork, S. Zauner, U.G. Maier, E. Hüllermeier, J. Bioinformatics and Computational Biology 12 (2014).
LibreCat
 
[245]
2014 | Journal Article | LibreCat-ID: 10313
Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track
T. Calders, F. Esposito, E. Hüllermeier, R. Meo, Machine Learning 97 (2014) 1–3.
LibreCat
 
[244]
2014 | Journal Article | LibreCat-ID: 10314
Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm
R. Busa-Fekete, B. Szörényi, P. Weng, W. Cheng, E. Hüllermeier, Machine Learning 97 (2014) 327–351.
LibreCat
 
[243]
2014 | Journal Article | LibreCat-ID: 10315
Dependent binary relevance models for multi-label classification
E. Montanés, R. Senge, J. Barranquero, J.R. Quevedo, J.J. Del Coz, E. Hüllermeier, Pattern Recognition 47 (2014) 1494–1508.
LibreCat
 
[242]
2014 | Journal Article | LibreCat-ID: 10316
Open challenges for data stream mining research
G. Krempl, I. Zliobaite, D. Brzezinski, E. Hüllermeier, M. Last, V. Lemaire, T. Noack, A. Shaker, S. Sievi, M. Spiliopoulou, J. Stefanowski, SIGKDD Explorations 16 (2014) 1–10.
LibreCat
 
[241]
2014 | Journal Article | LibreCat-ID: 10317
Extended Graph-Based Models for Enhanced Similarity Search in Cavbase
T. Krotzky, T. Fober, E. Hüllermeier, G. Klebe, IEEE/ACM Trans. Comput. Biology Bioinform. 11 (2014) 878–890.
LibreCat
 
[240]
2014 | Journal Article | LibreCat-ID: 10318
Identification of Functionally Releated Enzymes by Learning to Rank Methods
M. Stock, T. Fober, E. Hüllermeier, S. Glinca, G. Klebe, T. Pahikkala, A. Airola, B. De Baets, W. Wageman, IEEE/ACM Trans. Comput. Biology Bioinform. 11 (2014) 1157–1169.
LibreCat
 

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[439]
2024 | Journal Article | LibreCat-ID: 53073
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, Proceedings of the AAAI Conference on Artificial Intelligence 38 (2024) 14388–14396.
LibreCat | DOI
 
[438]
2023 | Preprint | LibreCat-ID: 44512 | OA
Detecting Novelties with Empty Classes
S. Uhlemeyer, J. Lienen, E. Hüllermeier, H. Gottschalk, ArXiv:2305.00983 (2023).
LibreCat | Download (ext.) | arXiv
 
[437]
2023 | Conference Paper | LibreCat-ID: 31880 | OA
Memorization-Dilation: Modeling Neural Collapse Under Noise
D.A. Nguyen, R. Levie, J. Lienen, G. Kutyniok, E. Hüllermeier, in: International Conference on Learning Representations, ICLR, 2023.
LibreCat | Download (ext.)
 
[436]
2023 | Book Chapter | LibreCat-ID: 45884 | OA
Configuration and Evaluation
J.M. Hanselle, E. Hüllermeier, F. Mohr, A.-C. Ngonga Ngomo, M. Sherif, A. Tornede, M.D. Wever, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 85–104.
LibreCat | Files available | DOI
 
[435]
2023 | Book Chapter | LibreCat-ID: 45886 | OA
Composition Analysis in Unknown Contexts
H. Wehrheim, E. Hüllermeier, S. Becker, M. Becker, C. Richter, A. Sharma, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 105–123.
LibreCat | Files available | DOI
 
[434]
2023 | Preprint | LibreCat-ID: 45911 | OA
Mitigating Label Noise through Data Ambiguation
J. Lienen, E. Hüllermeier, ArXiv:2305.13764 (2023).
LibreCat | Download (ext.) | arXiv
 
[433]
2023 | Journal Article | LibreCat-ID: 21600
Efficient time stepping for numerical integration using reinforcement learning
M. Dellnitz, E. Hüllermeier, M. Lücke, S. Ober-Blöbaum, C. Offen, S. Peitz, K. Pfannschmidt, SIAM Journal on Scientific Computing 45 (2023) A579–A595.
LibreCat | Files available | DOI | Download (ext.) | arXiv
 
[432]
2023 | Conference Paper | LibreCat-ID: 51373
Probabilistic Scoring Lists for Interpretable Machine Learning
J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, in: 26th International Conference on Discovery Science , Springer Nature Switzerland, Cham, 2023, pp. 189–203.
LibreCat | DOI
 
[431]
2023 | Book Chapter | LibreCat-ID: 48776
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, Cham, 2023.
LibreCat | DOI
 
[430]
2023 | Book Chapter | LibreCat-ID: 48778
iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios
M. Muschalik, F. Fumagalli, R. Jagtani, B. Hammer, E. Huellermeier, in: Communications in Computer and Information Science, Springer Nature Switzerland, Cham, 2023.
LibreCat | DOI
 
[429]
2023 | Conference Paper | LibreCat-ID: 48775
On Feature Removal for Explainability in Dynamic Environments
F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, in: ESANN 2023 Proceedings, i6doc.com publ., 2023.
LibreCat | DOI
 
[428]
2023 | Conference Paper | LibreCat-ID: 52230
SHAP-IQ: Unified Approximation of any-order Shapley Interactions
F. Fumagalli, M. Muschalik, P. Kolpaczki, E. Hüllermeier, B. Hammer, in: NeurIPS 2023 - Advances in Neural Information Processing Systems, Curran Associates, Inc., 2023, pp. 11515--11551.
LibreCat
 
[427]
2022 | Preprint | LibreCat-ID: 30868
A Survey of Methods for Automated Algorithm Configuration
E. Schede, J. Brandt, A. Tornede, M.D. Wever, V. Bengs, E. Hüllermeier, K. Tierney, ArXiv:2202.01651 (2022).
LibreCat | arXiv
 
[426]
2022 | Conference Paper | LibreCat-ID: 32311
Property-Driven Testing of Black-Box Functions
A. Sharma, V. Melnikov, E. Hüllermeier, H. Wehrheim, in: Proceedings of the 10th IEEE/ACM International Conference on Formal Methods in Software Engineering (FormaliSE), IEEE, 2022, pp. 113–123.
LibreCat
 
[425]
2022 | Conference Paper | LibreCat-ID: 34542
Scikit-Weak: A Python Library for Weakly Supervised Machine Learning
A. Campagner, J. Lienen, E. Hüllermeier, D. Ciucci, in: Lecture Notes in Computer Science, Springer, 2022, pp. 57–70.
LibreCat
 
[424]
2022 | Preprint | LibreCat-ID: 31546 | OA
Conformal Credal Self-Supervised Learning
J. Lienen, C. Demir, E. Hüllermeier, ArXiv:2205.15239 (2022).
LibreCat | Download (ext.)
 
[423]
2022 | Preprint | LibreCat-ID: 30867
Machine Learning for Online Algorithm Selection under Censored Feedback
A. Tornede, V. Bengs, E. Hüllermeier, Proceedings of the 36th AAAI Conference on Artificial Intelligence (2022).
LibreCat | arXiv
 
[422]
2022 | Preprint | LibreCat-ID: 30865
Algorithm Selection on a Meta Level
A. Tornede, L. Gehring, T. Tornede, M.D. Wever, E. Hüllermeier, Machine Learning (2022).
LibreCat | arXiv
 
[421]
2022 | Journal Article | LibreCat-ID: 33090
A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials
K. Gevers, A. Tornede, M.D. Wever, V. Schöppner, E. Hüllermeier, Welding in the World (2022).
LibreCat | DOI
 
[420]
2022 | Report | LibreCat-ID: 36227
Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens
B. Hammer, E. Hüllermeier, V. Lohweg, A. Schneider, W. Schenck, U. Kuhl, M. Braun, A. Pfeifer, C.-A. Holst, M. Schmidt, G. Schomaker, T. Tornede, Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens, 2022.
LibreCat | DOI
 
[419]
2022 | Journal Article | LibreCat-ID: 48780
Agnostic Explanation of Model Change based on Feature Importance
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, KI - Künstliche Intelligenz 36 (2022) 211–224.
LibreCat | DOI
 
[418]
2021 | Journal Article | LibreCat-ID: 24143
Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs!
J.P. Drees, P. Gupta, E. Hüllermeier, T. Jager, A. Konze, C. Priesterjahn, A. Ramaswamy, J. Somorovsky, 14th ACM Workshop on Artificial Intelligence and Security (2021).
LibreCat
 
[417]
2021 | Journal Article | LibreCat-ID: 24148
Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis
A. Ramaswamy, E. Hüllermeier, IEEE Transactions on Artificial Intelligence (to Appear) (2021).
LibreCat
 
[416]
2021 | Journal Article | LibreCat-ID: 21004
AutoML for Multi-Label Classification: Overview and Empirical Evaluation
M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1.
LibreCat | DOI
 
[415]
2021 | Journal Article | LibreCat-ID: 21092
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning
F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (n.d.).
LibreCat
 
[414]
2021 | Conference Paper | LibreCat-ID: 21570
Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance
T. Tornede, A. Tornede, M.D. Wever, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, 2021.
LibreCat
 
[413]
2021 | Journal Article | LibreCat-ID: 21636
Instance weighting through data imprecisiation
J. Lienen, E. Hüllermeier, International Journal of Approximate Reasoning (2021).
LibreCat | Download (ext.)
 
[412]
2021 | Conference Paper | LibreCat-ID: 21637 | OA
From Label Smoothing to Label Relaxation
J. Lienen, E. Hüllermeier, in: Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI, AAAI Press, 2021, pp. 8583–8591.
LibreCat | Download (ext.)
 
[411]
2021 | Conference Paper | LibreCat-ID: 23779
A Meta-Review on Artificial Intelligence in Product Creation
R. Bernijazov, A. Dicks, R. Dumitrescu, M. Foullois, J.M. Hanselle, E. Hüllermeier, G. Karakaya, P. Ködding, V. Lohweg, M. Malatyali, F. Meyer auf der Heide, M. Panzner, C. Soltenborn, in: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 2021.
LibreCat | Download (ext.)
 
[410]
2021 | Conference Paper | LibreCat-ID: 22280
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model
J. Lienen, E. Hüllermeier, R. Ewerth, N. Nommensen, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2021, pp. 14595–14604.
LibreCat
 
[409]
2021 | Preprint | LibreCat-ID: 22509 | OA
Credal Self-Supervised Learning
J. Lienen, E. Hüllermeier, ArXiv:2106.11853 (2021).
LibreCat | Download (ext.)
 
[408]
2021 | Conference Paper | LibreCat-ID: 22913
Automated Machine Learning, Bounded Rationality, and Rational Metareasoning
E. Hüllermeier, F. Mohr, A. Tornede, M.D. Wever, in: 2021.
LibreCat
 
[407]
2021 | Conference Paper | LibreCat-ID: 27381
Ranking Structured Objects with Graph Neural Networks
C. Damke, E. Hüllermeier, in: C. Soares, L. Torgo (Eds.), Proceedings of The 24th International Conference on Discovery Science (DS 2021), Springer, 2021, pp. 166–180.
LibreCat | DOI | arXiv
 
[406]
2021 | Preprint | LibreCat-ID: 30866
Towards Green Automated Machine Learning: Status Quo and Future Directions
T. Tornede, A. Tornede, J.M. Hanselle, M.D. Wever, F. Mohr, E. Hüllermeier, ArXiv:2111.05850 (2021).
LibreCat | arXiv
 
[405]
2021 | Conference Paper | LibreCat-ID: 21198 LibreCat
 
[404]
2021 | Book Chapter | LibreCat-ID: 29292 | OA
Drift Detection in Text Data with Document Embeddings
R. Feldhans, A. Wilke, S. Heindorf, M.H. Shaker, B. Hammer, A.-C. Ngonga Ngomo, E. Hüllermeier, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer International Publishing, Cham, 2021.
LibreCat | Files available | DOI | Download (ext.)
 
[403]
2021 | Working Paper | LibreCat-ID: 45616
Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes
D. van Straaten, V. Melnikov, E. Hüllermeier, B. Mir Djawadi, R. Fahr, Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes, 2021.
LibreCat
 
[402]
2021 | Journal Article | LibreCat-ID: 24456 | OA
Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems
K.J. Rohlfing, P. Cimiano, I. Scharlau, T. Matzner, H.M. Buhl, H. Buschmeier, E. Esposito, A. Grimminger, B. Hammer, R. Haeb-Umbach, I. Horwath, E. Hüllermeier, F. Kern, S. Kopp, K. Thommes, A.-C. Ngonga Ngomo, C. Schulte, H. Wachsmuth, P. Wagner, B. Wrede, IEEE Transactions on Cognitive and Developmental Systems 13 (2021) 717–728.
LibreCat | Files available | DOI
 
[401]
2020 | Preprint | LibreCat-ID: 19603 | OA
Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control
H. Bode, S.H. Heid, D. Weber, E. Hüllermeier, O. Wallscheid, ArXiv:2005.04869 (2020).
LibreCat | Download (ext.)
 
[400]
2020 | Conference Paper | LibreCat-ID: 19953 | OA
A Novel Higher-order Weisfeiler-Lehman Graph Convolution
C. Damke, V. Melnikov, E. Hüllermeier, in: S. Jialin Pan, M. Sugiyama (Eds.), Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020), PMLR, Bangkok, Thailand, 2020, pp. 49–64.
LibreCat | Files available | arXiv
 
[399]
2020 | Preprint | LibreCat-ID: 20211 | OA
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model
J. Lienen, E. Hüllermeier, ArXiv:2010.13118 (2020).
LibreCat | Download (ext.)
 
[398]
2020 | Conference Paper | LibreCat-ID: 24146
Constrained Multi-Agent Optimization with Unbounded Information Delay
S.H. Heid, A. Ramaswamy, E. Hüllermeier, in: Proceedings-30. Workshop Computational Intelligence: Berlin, 26.-27. November 2020, 2020, p. 247.
LibreCat
 
[397]
2020 | Conference Paper | LibreCat-ID: 17407
Extreme Algorithm Selection with Dyadic Feature Representation
A. Tornede, M.D. Wever, E. Hüllermeier, in: Discovery Science, 2020.
LibreCat
 
[396]
2020 | Conference Paper | LibreCat-ID: 17408
Hybrid Ranking and Regression for Algorithm Selection
J.M. Hanselle, A. Tornede, M.D. Wever, E. Hüllermeier, in: KI 2020: Advances in Artificial Intelligence, 2020.
LibreCat
 
[395]
2020 | Conference Paper | LibreCat-ID: 17424
AutoML for Predictive Maintenance: One Tool to RUL Them All
T. Tornede, A. Tornede, M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the ECMLPKDD 2020, 2020.
LibreCat | DOI
 
[394]
2020 | Preprint | LibreCat-ID: 17605 | OA
Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction
S.H. Heid, M.D. Wever, E. Hüllermeier, Journal of Data Mining and Digital Humanities (n.d.).
LibreCat | Download (ext.)
 
[393]
2020 | Conference Paper | LibreCat-ID: 20306
Towards Meta-Algorithm Selection
A. Tornede, M.D. Wever, E. Hüllermeier, in: Workshop MetaLearn 2020 @ NeurIPS 2020, 2020.
LibreCat
 
[392]
2020 | Book Chapter | LibreCat-ID: 18014
Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach
A. El Mesaoudi-Paul, D. Weiß, V. Bengs, E. Hüllermeier, K. Tierney, in: Learning and Intelligent Optimization. LION 2020., Springer, Cham, 2020, pp. 216–232.
LibreCat | DOI
 
[391]
2020 | Preprint | LibreCat-ID: 18017
Online Preselection with Context Information under the Plackett-Luce Model
A. El Mesaoudi-Paul, V. Bengs, E. Hüllermeier, ArXiv:2002.04275 (n.d.).
LibreCat
 
[390]
2020 | Conference Paper | LibreCat-ID: 18276
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis
A. Tornede, M.D. Wever, S. Werner, F. Mohr, E. Hüllermeier, in: ACML 2020, 2020.
LibreCat | Download (ext.)
 
[389]
2020 | Journal Article | LibreCat-ID: 16725
Algorithm Selection for Software Validation Based on Graph Kernels
C. Richter, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, Journal of Automated Software Engineering (n.d.).
LibreCat
 
[388]
2020 | Conference Paper | LibreCat-ID: 15629
LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification
M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, in: Springer, n.d.
LibreCat
 
[387]
2019 | Conference Abstract | LibreCat-ID: 8868
Towards Automated Machine Learning for Multi-Label Classification
M.D. Wever, F. Mohr, E. Hüllermeier, A. Hetzer, in: 2019.
LibreCat | Files available
 
[386]
2019 | Journal Article | LibreCat-ID: 10578
Choice Functions Generated by Mallows and Plackett–Luce Relations
V.K. Tagne, S. Fotso, L.A. Fono, E. Hüllermeier, New Mathematics and Natural Computation 15 (2019) 191–213.
LibreCat
 
[385]
2019 | Journal Article | LibreCat-ID: 15001
Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning
I. Couso, C. Borgelt, E. Hüllermeier, R. Kruse, IEEE Computational Intelligence Magazine (2019) 31–44.
LibreCat | DOI
 
[384]
2019 | Journal Article | LibreCat-ID: 15002 | OA
Multi-target prediction: a unifying view on problems and methods
W. Waegeman, K. Dembczynski, E. Hüllermeier, Data Mining and Knowledge Discovery 33 (2019) 293–324.
LibreCat | Files available | DOI
 
[383]
2019 | Conference Paper | LibreCat-ID: 15003
Set-Valued Prediction in Multi-Class Classification
T. Mortier, M. Wydmuch, K. Dembczynski, E. Hüllermeier, W. Waegeman, in: Proceedings of the 31st Benelux Conference on Artificial Intelligence {(BNAIC} 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019, 2019.
LibreCat
 
[382]
2019 | Book Chapter | LibreCat-ID: 15004
Feature Selection for Analogy-Based Learning to Rank
M. Ahmadi Fahandar, E. Hüllermeier, in: Discovery Science, Cham, 2019.
LibreCat | DOI
 
[381]
2019 | Book Chapter | LibreCat-ID: 15005
Analogy-Based Preference Learning with Kernels
M. Ahmadi Fahandar, E. Hüllermeier, in: KI 2019: Advances in Artificial Intelligence, Cham, 2019.
LibreCat | DOI
 
[380]
2019 | Book Chapter | LibreCat-ID: 15006
Epistemic Uncertainty Sampling
V.-L. Nguyen, S. Destercke, E. Hüllermeier, in: Discovery Science, Cham, 2019.
LibreCat | DOI
 
[379]
2019 | Conference Paper | LibreCat-ID: 15007 | OA
Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA
V. Melnikov, E. Hüllermeier, in: Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101), 2019.
LibreCat | Files available | DOI
 
[378]
2019 | Conference Paper | LibreCat-ID: 15011 | OA
Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking
A. Tornede, M.D. Wever, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, KIT Scientific Publishing, Karlsruhe, 2019, pp. 135–146.
LibreCat | Files available
 
[377]
2019 | Conference Paper | LibreCat-ID: 15013
A Reduction of Label Ranking to Multiclass Classification
K. Brinker, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Würzburg, Germany, 2019.
LibreCat
 
[376]
2019 | Conference Paper | LibreCat-ID: 15014
Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants
E. Hüllermeier, I. Couso, S. Diestercke, in: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.
LibreCat
 
[375]
2019 | Journal Article | LibreCat-ID: 15015
Mining Rank Data
S. Henzgen, E. Hüllermeier, ACM Transactions on Knowledge Discovery from Data (2019) 1–36.
LibreCat | DOI
 
[374]
2019 | Conference Abstract | LibreCat-ID: 13132
From Automated to On-The-Fly Machine Learning
F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, in: INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft, Gesellschaft für Informatik e.V., Bonn, 2019, pp. 273–274.
LibreCat
 
[373]
2019 | Conference Paper | LibreCat-ID: 10232 | OA
Automating Multi-Label Classification Extending ML-Plan
M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.
LibreCat | Files available
 
[372]
2019 | Journal Article | LibreCat-ID: 20243
Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches
K. Rohlfing, G. Leonardi, I. Nomikou, J. Rączaszek-Leonardi, E. Hüllermeier, IEEE Transactions on Cognitive and Developmental Systems (2019).
LibreCat | DOI
 
[371]
2018 | Conference Paper | LibreCat-ID: 2479 | OA
(WIP) Towards the Automated Composition of Machine Learning Services
F. Mohr, M.D. Wever, E. Hüllermeier, A. Faez, in: SCC, IEEE, San Francisco, CA, USA, 2018.
LibreCat | Files available | DOI | Download (ext.)
 
[370]
2018 | Conference Paper | LibreCat-ID: 2857 | OA
Programmatic Task Network Planning
F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39.
LibreCat | Files available | Download (ext.)
 
[369]
2018 | Conference Paper | LibreCat-ID: 2471 | OA
On-The-Fly Service Construction with Prototypes
F. Mohr, M.D. Wever, E. Hüllermeier, in: SCC, IEEE Computer Society, San Francisco, CA, USA, 2018.
LibreCat | Files available | DOI | Download (ext.)
 
[368]
2018 | Journal Article | LibreCat-ID: 3402 LibreCat | Files available | DOI
 
[367]
2018 | Journal Article | LibreCat-ID: 3510 | OA
ML-Plan: Automated Machine Learning via Hierarchical Planning
F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning (2018) 1495–1515.
LibreCat | Files available | DOI | Download (ext.)
 
[366]
2018 | Conference Paper | LibreCat-ID: 3552 | OA
Reduction Stumps for Multi-Class Classification
F. Mohr, M.D. Wever, E. Hüllermeier, in: Proceedings of the Symposium on Intelligent Data Analysis, ‘s-Hertogenbosch, the Netherlands, n.d.
LibreCat | Files available | DOI | Download (ext.)
 
[365]
2018 | Conference Paper | LibreCat-ID: 3852 | OA
ML-Plan for Unlimited-Length Machine Learning Pipelines
M.D. Wever, F. Mohr, E. Hüllermeier, in: ICML 2018 AutoML Workshop, 2018.
LibreCat | Files available | Download (ext.)
 
[364]
2018 | Conference Paper | LibreCat-ID: 2109 | OA
Ensembles of Evolved Nested Dichotomies for Classification
M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, Kyoto, Japan, 2018.
LibreCat | Files available | DOI | Download (ext.)
 
[363]
2018 | Preprint | LibreCat-ID: 17713 | OA
Automated Multi-Label Classification based on ML-Plan
M.D. Wever, F. Mohr, E. Hüllermeier, (2018).
LibreCat | Download (ext.)
 
[362]
2018 | Preprint | LibreCat-ID: 17714 | OA
Automated machine learning service composition
F. Mohr, M.D. Wever, E. Hüllermeier, (2018).
LibreCat | Download (ext.)
 
[361]
2018 | Book Chapter | LibreCat-ID: 6423
Preference-Based Reinforcement Learning Using Dyad Ranking
D. Schäfer, E. Hüllermeier, in: Discovery Science, Springer International Publishing, Cham, 2018, pp. 161–175.
LibreCat | Files available | DOI
 
[360]
2018 | Conference (Editor) | LibreCat-ID: 10591
Research Directions for Principles of Data Management
S. Abiteboul, M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David, R. Hull, E. Hüllermeier, B. Kimelfeld, L. Libkin, W. Martens, T. Milo, F. Murlak, F. Neven, M. Ortiz, T. Schwentick, J. Stoyanovich, J. Su, D. Suciu, V. Vianu, K. Yi, eds., Research Directions for Principles of Data Management, 2018.
LibreCat
 
[359]
2018 | Book Chapter | LibreCat-ID: 10783
Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators
I. Couso, E. Hüllermeier, in: S. Mostaghim, A. Nürnberger, C. Borgelt (Eds.), Frontiers in Computational Intelligence, Springer, 2018, pp. 31–46.
LibreCat
 
[358]
2018 | Journal Article | LibreCat-ID: 16038
Dyad ranking using Plackett-Luce models based on joint feature representations
D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941.
LibreCat
 
[357]
2018 | Conference Paper | LibreCat-ID: 10145
Learning to Rank Based on Analogical Reasoning
M. Ahmadi Fahandar, E. Hüllermeier, in: Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2018, pp. 2951–2958.
LibreCat
 
[356]
2018 | Conference Paper | LibreCat-ID: 10148
Ranking Distributions based on Noisy Sorting
A. El Mesaoudi-Paul, E. Hüllermeier, R. Busa-Fekete, in: Proc. 35th Int. Conference on Machine Learning (ICML), Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018, pp. 3469–3477.
LibreCat
 
[355]
2018 | Conference Paper | LibreCat-ID: 10149
A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart
M. Hesse, J. Timmermann, E. Hüllermeier, A. Trächtler, in: Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 2018, pp. 15–20.
LibreCat
 
[354]
2018 | Book Chapter | LibreCat-ID: 10152
Learning interpretable rules for multi-label classification
E.L. Mencia, J. Fürnkranz, E. Hüllermeier, M. Rapp, in: H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, M.A.J. van Gerven (Eds.), Explainable and Interpretable Models in Computer Vision and Machine Learning, Springer, 2018, pp. 81–113.
LibreCat
 
[353]
2018 | Conference Paper | LibreCat-ID: 10181
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty
V.-L. Nguyen, S. Destercke, M.-H. Masson, E. Hüllermeier, in: Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095.
LibreCat
 
[352]
2018 | Conference Paper | LibreCat-ID: 10184
Preference-Based Reinforcement Learning Using Dyad Ranking
D. Schäfer, E. Hüllermeier, in: Proc. 21st Int. Conference on Discovery Science (DS), 2018, pp. 161–175.
LibreCat
 
[351]
2018 | Journal Article | LibreCat-ID: 10276
Dyad Ranking Using Plackett-Luce Models based on joint feature representations
D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941.
LibreCat
 
[350]
2018 | Conference Abstract | LibreCat-ID: 1379 | OA
Supporting the Cognitive Process in Annotation Tasks
N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M.D. Wever, E. Hüllermeier, in: K. Eckart, D. Schlechtweg (Eds.), Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, 2018.
LibreCat | Files available | Download (ext.)
 
[349]
2018 | Journal Article | LibreCat-ID: 22996
A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart
M. Hesse, J. Timmermann, E. Hüllermeier, A. Trächtler, Procedia Manufacturing 24 (2018) 15–20.
LibreCat
 
[348]
2017 | Conference Paper | LibreCat-ID: 3325
Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics
V. Melnikov, E. Hüllermeier, in: Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing, 2017.
LibreCat | Files available | DOI
 
[347]
2017 | Conference Paper | LibreCat-ID: 71
Predicting Rankings of Software Verification Tools
M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proceedings of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26.
LibreCat | Files available | DOI
 
[346]
2017 | Report | LibreCat-ID: 72
Predicting Rankings of Software Verification Competitions
M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, Predicting Rankings of Software Verification Competitions, 2017.
LibreCat | Files available
 
[345]
2017 | Encyclopedia Article | LibreCat-ID: 10589
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: Encyclopedia of Machine Learning and Data Mining, 2017, pp. 1000–1005.
LibreCat
 
[344]
2017 | Book Chapter | LibreCat-ID: 10784
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2017, pp. 1000–1005.
LibreCat
 
[343]
2017 | Conference Paper | LibreCat-ID: 1180 | OA
Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization
M.D. Wever, F. Mohr, E. Hüllermeier, in: 27th Workshop Computational Intelligence, Dortmund, 2017.
LibreCat | Files available | Download (ext.)
 
[342]
2017 | Conference Paper | LibreCat-ID: 15397
Optimizing the structure of nested dichotomies. A comparison of two heuristics
V. Melnikov, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, KIT Scientific Publishing, 2017, pp. 1–12.
LibreCat
 
[341]
2017 | Conference Paper | LibreCat-ID: 15399
Predicting rankings of software verification tools
M. Czech, E. Hüllermeier, M.C. Jacobs, H. Wehrheim, in: In Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany, 2017.
LibreCat
 
[340]
2017 | Conference Paper | LibreCat-ID: 15110
Maximum likelihood estimation and coarse data
I. Couso, D. Dubois, E. Hüllermeier, in: In Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain, Springer, 2017, pp. 3–16.
LibreCat
 
[339]
2017 | Conference Paper | LibreCat-ID: 10204
Estimating relative depth in single images via rankboost
R. Ewerth, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok, K. Dembczynski, E. Hüllermeier, in: Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 2017, pp. 919–924.
LibreCat
 
[338]
2017 | Conference Paper | LibreCat-ID: 10205
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
M. Ahmadi Fahandar, E. Hüllermeier, I. Couso, in: Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 2017, pp. 1078–1087.
LibreCat
 
[337]
2017 | Conference Paper | LibreCat-ID: 10206 | OA
Planning with Independent Task Networks
F. Mohr, T. Lettmann, E. Hüllermeier, in: Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017), 2017, pp. 193–206.
LibreCat | Files available | DOI
 
[336]
2017 | Conference Paper | LibreCat-ID: 10207
Predicting rankings of software verification tools
M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 2017, pp. 23–26.
LibreCat
 
[335]
2017 | Conference Paper | LibreCat-ID: 10208
Maximum Likelihood Estimation and Coarse Data
I. Couso, D. Dubois, E. Hüllermeier, in: Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 2017, pp. 3–16.
LibreCat
 
[334]
2017 | Conference Paper | LibreCat-ID: 10209
Learning to Rank based on Analogical Reasoning
M. Ahmadi Fahandar, E. Hüllermeier, in: Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence, 2017.
LibreCat
 
[333]
2017 | Conference Paper | LibreCat-ID: 10212 LibreCat
 
[332]
2017 | Conference Paper | LibreCat-ID: 10213
Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics
V. Melnikov, E. Hüllermeier, in: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.
LibreCat
 
[331]
2017 | Conference Paper | LibreCat-ID: 10216
Learning TSK Fuzzy Rules from Data Streams
A. Shaker, W. Heldt, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.
LibreCat
 
[330]
2017 | Journal Article | LibreCat-ID: 10267
Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting
M. Bräuning, E. Hüllermeier, T. Keller, M. Glaum, European Journal of Operational Research 258 (2017) 295–306.
LibreCat
 
[329]
2017 | Journal Article | LibreCat-ID: 10268
Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic
M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions on Software Engineering 43 (2017) 739–759.
LibreCat
 
[328]
2017 | Journal Article | LibreCat-ID: 10269
From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection
E. Hüllermeier, The Computing Research Repository  (CoRR) (2017).
LibreCat
 
[327]
2016 | Journal Article | LibreCat-ID: 3318
Pairwise versus Pointwise Ranking: A Case Study
V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, Pritha Gupta, Schedae Informaticae 25 (2016).
LibreCat | Files available | DOI
 
[326]
2016 | Journal Article | LibreCat-ID: 190
Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic
M.C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017 (2016) 739–759.
LibreCat | Files available | DOI
 
[325]
2016 | Conference Paper | LibreCat-ID: 184
Learning to Aggregate Using Uninorms
V. Melnikov, E. Hüllermeier, in: Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771.
LibreCat | Files available | DOI
 
[324]
2016 | Encyclopedia Article | LibreCat-ID: 10785
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2016.
LibreCat
 
[323]
2016 | Conference Paper | LibreCat-ID: 15400
On the identifiability of models in multi-criteria preference learning
C. Labreuche, E. Hüllermeier, P. Vojtas, A. Fallah Tehrani, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.
LibreCat
 
[322]
2016 | Conference Paper | LibreCat-ID: 15401
Preference -based reinforcement learning using dyad ranking
D. Schäfer, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany, 2016.
LibreCat
 
[321]
2016 | Conference Paper | LibreCat-ID: 15402
Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators
I. Couso, M. Ahmadi Fahandar, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.
LibreCat
 
[320]
2016 | Conference Paper | LibreCat-ID: 15403
Support vector classification on noisy data using fuzzy superset losses
S. Lu, E. Hüllermeier, in: E. Hüllermeier, F. Hoffmann, R. Mikut (Eds.), In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, KIT Scientific Publishing, 2016, pp. 1–8.
LibreCat
 
[319]
2016 | Conference Paper | LibreCat-ID: 15404
Plackett-Luce networks for dyad ranking
D. Schäfer, E. Hüllermeier, in: In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016.
LibreCat
 
[318]
2016 | Conference Paper | LibreCat-ID: 15111
Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical concepts
K. Pfannschmidt, E. Hüllermeier, S. Held, R. Neiger, in: In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–461.
LibreCat
 
[317]
2016 | Journal Article | LibreCat-ID: 16041
CavSimBase: A database for large scale comparison of protein binding sites
M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, E. Hüllermeier, IEEE Transactions on Knowledge and Data Engineering 28 (2016) 1423–1434.
LibreCat
 
[316]
2016 | Book Chapter | LibreCat-ID: 10214
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2016.
LibreCat
 
[315]
2016 | Conference (Editor) | LibreCat-ID: 10221
Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany
F. Hoffmann, E. Hüllermeier, R. Mikut, eds., Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany, 2016.
LibreCat
 
[314]
2016 | Conference Paper | LibreCat-ID: 10222
Extreme F-measure maximization using sparse probability estimates
K. Jasinska, K. Dembczynski, R. Busa-Fekete, T. Klerx, E. Hüllermeier, in: M.F. Balcan, K.Q. Weinberger (Eds.), Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA, 2016.
LibreCat
 
[313]
2016 | Conference Paper | LibreCat-ID: 10223
Learning to aggregate using uninorms, in Proceedings ECML/PKDD-2016
V. Melnikov, E. Hüllermeier, in: European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 756–771.
LibreCat
 
[312]
2016 | Conference Paper | LibreCat-ID: 10224
Consistency of probalistic classifier trees
K. Dembczynski, W. Kotlowski, W. Waegeman, R. Busa-Fekete, E. Hüllermeier, in: In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 511–526.
LibreCat
 
[311]
2016 | Conference Paper | LibreCat-ID: 10225
Predicting the electricity consumption of buildings: An improved CBR approach
A. Shabani, A. Paul, R. Platon, E. Hüllermeier, in: In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 2016, pp. 356–369.
LibreCat
 
[310]
2016 | Conference Paper | LibreCat-ID: 10226
Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical concepts
K. Pfannschmidt, E. Hüllermeier, S. Held, R. Neiger, in: In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–461.
LibreCat
 
[309]
2016 | Conference Paper | LibreCat-ID: 10227
On the Identifiability of models in multi-criteria preference learning
C. Labreuche, E. Hüllermeier, P. Vojtas, A. Fallah Tehrani, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.
LibreCat
 
[308]
2016 | Conference Paper | LibreCat-ID: 10228
Preference-Based Reinforcement Learning Using Dyad Ranking
D. Schäfer, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.
LibreCat
 
[307]
2016 | Conference Paper | LibreCat-ID: 10229
Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators
I. Couso, M. Ahmadi Fahandar, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.
LibreCat
 
[306]
2016 | Conference Paper | LibreCat-ID: 10230
Support vector classification on noisy data using fuzzy supersets losses
S. Lu, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing, 2016, pp. 1–8.
LibreCat
 
[305]
2016 | Conference Paper | LibreCat-ID: 10231
Plackett-Luce networks for dyad ranking
D. Schäfer, E. Hüllermeier, in: In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016.
LibreCat
 
[304]
2016 | Conference (Editor) | LibreCat-ID: 10263
ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial Intelligence
G.A. Kaminka, M. Fox, P. Bouquet, E. Hüllermeier, V. Dignum, F. Dignum, F. van Harmelen, eds., ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence, IOS Press, The Hague, The Netherlands, 2016.
LibreCat
 
[303]
2016 | Journal Article | LibreCat-ID: 10264
CavSimBase: A database for large scale comparison of protein binding sites
M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, E. Hüllermeier, IEEE Transactions on Knowledge and Data Engineering 28 (2016) 1423–1434.
LibreCat
 
[302]
2016 | Journal Article | LibreCat-ID: 10266 LibreCat
 
[301]
2015 | Journal Article | LibreCat-ID: 4792
Fast Fuzzy Pattern Tree Learning for Classification
R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.
LibreCat | Files available | DOI
 
[300]
2015 | Conference Paper | LibreCat-ID: 15406
Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations
D. Schäfer, E. Hüllermeier, in: In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located ECML/PKDD, Porto, Portugal, 2015, pp. 110–111.
LibreCat
 
[299]
2015 | Conference Paper | LibreCat-ID: 15749
A cbr approach to the angry birds game
A. Paul, E. Hüllermeier, in: In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany, 2015, pp. 68–77.
LibreCat
 
[298]
2015 | Conference Paper | LibreCat-ID: 15750
Depth estimation in monocular images: Quantitative versus qualitative approaches
R. Ewerth, A. Balz, J. Gehlhaar, K. Dembczynski, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier (Eds.), In Proceedings 25. Workshop Computational Intelligence, Dortmund, Germany, KIT Scientific Publishing, 2015, pp. 235–240.
LibreCat
 
[297]
2015 | Conference Paper | LibreCat-ID: 15751
Locally weighted regression through data imprecisiation
S. Lu, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier (Eds.), In Proceedings 25th Workshop Computational Intelligence, Dortmund Germany, KIT Scientific Publishing, 2015, pp. 97–104.
LibreCat
 
[296]
2015 | Journal Article | LibreCat-ID: 16049
Fast fuzzy pattern tree learning for classification
R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.
LibreCat
 
[295]
2015 | Journal Article | LibreCat-ID: 16051 LibreCat
 
[294]
2015 | Journal Article | LibreCat-ID: 16053
Does machine learning need fuzzy logic?
E. Hüllermeier, Fuzzy Sets and Systems 281 (2015) 292–299.
LibreCat
 
[293]
2015 | Journal Article | LibreCat-ID: 16058
On the Bayes-optimality of F-measure maximizers
W. Waegeman, K. Dembczynski, A. Jachnik, W. Cheng, E. Hüllermeier, Journal of Machine Learning Research 15 (2015) 3313–3368.
LibreCat
 
[292]
2015 | Journal Article | LibreCat-ID: 16067 LibreCat
 
[291]
2015 | Conference Paper | LibreCat-ID: 10234
Case-Based Reasoning Research and Development
E. Hüllermeier, M. Minor, in: In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015) LNAI 9343, Springer, 2015.
LibreCat
 
[290]
2015 | Conference Paper | LibreCat-ID: 10235 LibreCat
 
[289]
2015 | Conference Paper | LibreCat-ID: 10236
Case Base Maintenance in Preference-Based CBR
A. Abdel-Aziz, E. Hüllermeier, in: In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 1–14.
LibreCat
 
[288]
2015 | Conference Paper | LibreCat-ID: 10237
Qualitative Multi-Armed Bandits: A Quantile-Based Approach
B. Szörényi, R. Busa-Fekete, P. Weng, E. Hüllermeier, in: In Proceedings International Conference on Machine Learning (ICML 2015), 2015, pp. 1660–1668.
LibreCat
 
[287]
2015 | Conference Paper | LibreCat-ID: 10238
Dyad Ranking Using A Bilinear Plackett-Luce Model
D. Schäfer, E. Hüllermeier, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 227–242.
LibreCat
 
[286]
2015 | Conference Paper | LibreCat-ID: 10239
Superset Learning Based on Generalized Loss Minimization
E. Hüllermeier, W. Cheng, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 260–275.
LibreCat
 
[285]
2015 | Conference Paper | LibreCat-ID: 10240
Weighted Rank Correlation : A Flexible Approach Based on Fuzzy Order Relations
S. Henzgen, E. Hüllermeier, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 422–437.
LibreCat
 
[284]
2015 | Conference Paper | LibreCat-ID: 10241
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach
B. Szörényi, R. Busa-Fekete, A. Paul, E. Hüllermeier, in: In Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 604–612.
LibreCat
 
[283]
2015 | Conference Paper | LibreCat-ID: 10242
Online F-Measure Optimization
B. Szörényi, R. Busa-Fekete, K. Dembczynski, E. Hüllermeier, in: In Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 595–603.
LibreCat
 
[282]
2015 | Conference Paper | LibreCat-ID: 10243
A CBR Approach to the Angry Birds Game
A. El Mesaoudi-Paul, E. Hüllermeier, in: In Workshop Proc. 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 68–77.
LibreCat
 
[281]
2015 | Conference Paper | LibreCat-ID: 10244
Preference-Based Meta- Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations
D. Schäfer, E. Hüllermeier, in: In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel@PKDD/ECML), 2015, pp. 110–111.
LibreCat
 
[280]
2015 | Conference Paper | LibreCat-ID: 10245
Locally weighted regression through data imprecisiation
S. Lu, E. Hüllermeier, in: Proceedings 25. Workshop Computational Intelligence, 2015, pp. 97–104.
LibreCat
 
[279]
2015 | Conference Paper | LibreCat-ID: 10246
Depth estimation in monocular images: Quantitative versus qualitative approaches
R. Ewerth, A. Balz, J. Gehlhaar, K. Dembczynski, E. Hüllermeier, in: Proceedings 25. Workshop Computational Intelligence, 2015, pp. 235–240.
LibreCat
 
[278]
2015 | Journal Article | LibreCat-ID: 10319
On the Bayes-Optimality of F-Measure Maximizers
W. Waegeman, K. Dembczynski, A. Jachnik, W. Cheng, E. Hüllermeier, In Journal of Machine Learning Research 15 (2015) 3333–3388.
LibreCat
 
[277]
2015 | Journal Article | LibreCat-ID: 10320
Does machine learning need fuzzy logic?
E. Hüllermeier, Fuzzy Sets and Systems 281 (2015) 292–299.
LibreCat
 
[276]
2015 | Journal Article | LibreCat-ID: 10321 LibreCat
 
[275]
2015 | Journal Article | LibreCat-ID: 10322 LibreCat
 
[274]
2015 | Journal Article | LibreCat-ID: 10323
Overlap Indices: Construction of and Application of Interpolative Fuzzy Systems
S. Garcia-Jimenez, U. Bustince, E. Hüllermeier, R. Mesiar, N.R. Pal, A. Pradera, IEEE Transactions on Fuzzy Systems 23 (2015) 1259–1273.
LibreCat
 
[273]
2015 | Journal Article | LibreCat-ID: 10324
Fast Fuzzy Pattern Tree Learning of Classification
R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.
LibreCat
 
[272]
2014 | Journal Article | LibreCat-ID: 16046
Preference-based learning of ideal solutions in TOPSIS-like decision models
M. Agarwal, A. Fallah Tehrani, E. Hüllermeier, Journal of Multi-Criteria Decision Analysis 22 (2014).
LibreCat
 
[271]
2014 | Journal Article | LibreCat-ID: 16060
Extended graph-based models for enhanced similarity search in Cabase
T. Krotzky, T. Fober, E. Hüllermeier, G. Klebe, IEEE/ACM Transactions of Computational Biology and Bioinformatics 11 (2014) 878–890.
LibreCat
 
[270]
2014 | Journal Article | LibreCat-ID: 16064
Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization
E. Hüllermeier, International Journal of Approximate Reasoning 55 (2014) 1519–1534.
LibreCat
 
[269]
2014 | Journal Article | LibreCat-ID: 16069
Visualization of evolving fuzzy-rule-based systems
S. Henzgen, M. Strickert, E. Hüllermeier, Evolving Systems 5 (2014) 175–191.
LibreCat
 
[268]
2014 | Journal Article | LibreCat-ID: 16077
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm.
R. Busa-Fekete, B. Szörenyi, P. Weng, W. Cheng, E. Hüllermeier, Machine Learning 97 (2014) 327–351.
LibreCat
 
[267]
2014 | Journal Article | LibreCat-ID: 16078
Open challenges for data stream mining research
G. Krempl, I. Zliobaite, D. Brzezinski, E. Hüllermeier, M. Last, V. Lemaire, T. Noack, A. Shaker, S. Sievi, M. Spiliopoulou, J. Stefanowski, SIGKDD Explorations 16 (2014) 1–10.
LibreCat
 
[266]
2014 | Journal Article | LibreCat-ID: 16079
Correlation-based embedding of pairwise score data
M. Strickert, K. Bunte, F.M. Schleif, E. Hüllermeier, Neurocomputing 141 (2014) 97–109.
LibreCat
 
[265]
2014 | Journal Article | LibreCat-ID: 16080
Survival analysis on data streams: Analyzing temporal events in dynamically changing environments
A. Shaker, E. Hüllermeier, International Journal of Applied Mathematics and Computer Science 24 (2014) 199–212.
LibreCat
 
[264]
2014 | Journal Article | LibreCat-ID: 16082
Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty
R. Senge, S. Bösner, K. Dembczynski, J. Haasenritter, O. Hirsch, N. Donner-Banzhoff, E. Hüllermeier, Information Sciences 255 (2014) 16–29.
LibreCat
 
[263]
2014 | Journal Article | LibreCat-ID: 16083
The comprehensive diagnostic study is suggested as a design to model the diagnostic process
N. Donner-Banzhoff, J. Haasenritter, E. Hüllermeier, A. Viniol, S. Bösner, A. Becker, Journal of Clinical Epidemiology 2 (2014) 124–132.
LibreCat
 
[262]
2014 | Conference Paper | LibreCat-ID: 10247
PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences
R. Busa-Fekete, B. Szörényi, E. Hüllermeier, in: Proceedings AAAI 2014, Quebec, Canada, 2014, pp. 1701–1707.
LibreCat
 
[261]
2014 | Conference Paper | LibreCat-ID: 10248
A Survey of Preference-Based Online Learning with Bandit Algorithms
R. Busa-Fekete, E. Hüllermeier, in: Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia, 2014, pp. 18–39.
LibreCat
 
[260]
2014 | Conference Paper | LibreCat-ID: 10249
Mining Rank Data
S. Henzgen, E. Hüllermeier, in: Proceedings Discovery Science, Bled,Slovenia , 2014, pp. 123–134.
LibreCat
 
[259]
2014 | Conference Paper | LibreCat-ID: 10250
The Choquet kernel for monotone data
A. Fallah Tehrani, M. Strickert, E. Hüllermeier, in: Proceedings ESANN , Bruges, Belgium, 2014.
LibreCat
 
[258]
2014 | Conference Paper | LibreCat-ID: 10251
Learning Solution Similarity in Preference-Based CBR
A. Abdel-Aziz, M. Strickert, E. Hüllermeier, in: Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland, 2014, pp. 17–31.
LibreCat
 
[257]
2014 | Conference Paper | LibreCat-ID: 10253
Dyad Ranking Using A Bilinear Plackett-Luce Model
D. Schäfer, E. Hüllermeier, in: Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany, 2014, pp. 32–33.
LibreCat
 
[256]
2014 | Conference Paper | LibreCat-ID: 10254
Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France
T. Calders, F. Esposito, E. Hüllermeier, R. Meo, in: Proceedings, Parts I-III. Lecture Notes in Computer Science, Springer, 2014, pp. 8724–8726.
LibreCat
 
[255]
2014 | Conference Paper | LibreCat-ID: 10295
Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports
J. Fürnkranz, E. Hüllermeier, C. Rudin, R. Slowinski, S. Sanner, in: 2014, pp. 1–27.
LibreCat
 
[254]
2014 | Journal Article | LibreCat-ID: 10296
Survival analysis on data streams: Analyzing temporal events in dynamically changing environments
A. Shaker, E. Hüllermeier, Applied Mathematics and Computer Science 24 (2014) 199–212.
LibreCat
 
[253]
2014 | Journal Article | LibreCat-ID: 10297
Ausgewählte Beiträge des GMA-Fachausschusses 5.14
F. Hoffmann, E. Hüllermeier, A. Kroll, Computational Intelligence Automatisierungstechnik 62 (2014) 685–686.
LibreCat
 
[252]
2014 | Journal Article | LibreCat-ID: 10298
Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track
T. Calders, F. Esposito, E. Hüllermeier, R. Meo, Data Min. Knowledge Discovery 28 (2014) 1129–1133.
LibreCat
 
[251]
2014 | Journal Article | LibreCat-ID: 10299
Visualization of evolving fuzzy rule-based systems
S. Henzgen, M. Strickert, E. Hüllermeier, Evolving Systems 5 (2014) 175–191.
LibreCat
 
[250]
2014 | Journal Article | LibreCat-ID: 10308 LibreCat
 
[249]
2014 | Journal Article | LibreCat-ID: 10309 LibreCat
 
[248]
2014 | Journal Article | LibreCat-ID: 10310
Correlation-based embedding of pairwise score data
M. Strickert, K. Bunte, F.-M. Schleif, E. Hüllermeier, Neurocomputing 141 (2014) 97–109.
LibreCat
 
[247]
2014 | Journal Article | LibreCat-ID: 10311
Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty
R. Senge, S. Bösner, K. Dembczynski, J. Haasenritter, O. Hirsch, N. Donner-Banzhoff, E. Hüllermeier, Information Sciences 255 (2014) 16–29.
LibreCat
 
[246]
2014 | Journal Article | LibreCat-ID: 10312
Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances
M. Mernberger, M. Moog, S. Stork, S. Zauner, U.G. Maier, E. Hüllermeier, J. Bioinformatics and Computational Biology 12 (2014).
LibreCat
 
[245]
2014 | Journal Article | LibreCat-ID: 10313
Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track
T. Calders, F. Esposito, E. Hüllermeier, R. Meo, Machine Learning 97 (2014) 1–3.
LibreCat
 
[244]
2014 | Journal Article | LibreCat-ID: 10314
Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm
R. Busa-Fekete, B. Szörényi, P. Weng, W. Cheng, E. Hüllermeier, Machine Learning 97 (2014) 327–351.
LibreCat
 
[243]
2014 | Journal Article | LibreCat-ID: 10315
Dependent binary relevance models for multi-label classification
E. Montanés, R. Senge, J. Barranquero, J.R. Quevedo, J.J. Del Coz, E. Hüllermeier, Pattern Recognition 47 (2014) 1494–1508.
LibreCat
 
[242]
2014 | Journal Article | LibreCat-ID: 10316
Open challenges for data stream mining research
G. Krempl, I. Zliobaite, D. Brzezinski, E. Hüllermeier, M. Last, V. Lemaire, T. Noack, A. Shaker, S. Sievi, M. Spiliopoulou, J. Stefanowski, SIGKDD Explorations 16 (2014) 1–10.
LibreCat
 
[241]
2014 | Journal Article | LibreCat-ID: 10317
Extended Graph-Based Models for Enhanced Similarity Search in Cavbase
T. Krotzky, T. Fober, E. Hüllermeier, G. Klebe, IEEE/ACM Trans. Comput. Biology Bioinform. 11 (2014) 878–890.
LibreCat
 
[240]
2014 | Journal Article | LibreCat-ID: 10318
Identification of Functionally Releated Enzymes by Learning to Rank Methods
M. Stock, T. Fober, E. Hüllermeier, S. Glinca, G. Klebe, T. Pahikkala, A. Airola, B. De Baets, W. Wageman, IEEE/ACM Trans. Comput. Biology Bioinform. 11 (2014) 1157–1169.
LibreCat
 

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