122 Publications

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[122]
2019 | Conference Paper | LibreCat-ID: 10232
Automating Multi-Label Classification Extending ML-Plan
M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.
LibreCat | Files available
 
[121]
2019 | Conference Abstract | LibreCat-ID: 8956
Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking
A. Hetzer, M.D. Wever, F. Mohr, E. Hüllermeier, in: 2019.
LibreCat | Files available
 
[120]
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
 
[119]
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.
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[118]
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
 
[117]
2018 | Conference Paper | LibreCat-ID: 3852
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.)
 
[116]
2018 | Conference Paper | LibreCat-ID: 2479
(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.)
 
[115]
2018 | Conference Paper | LibreCat-ID: 10153
Reduction Stumps for Multi-class Classification
F. Mohr, M.D. Wever, E. Hüllermeier, in: Proc. 17th Int. Symposium on Intelligent Data Analysis (IDA), 2018, pp. 225–237.
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[114]
2018 | Conference Paper | LibreCat-ID: 10185
Supporting the Cognitive Process in Annotation Tasks
N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M.D. Wever, E. Hüllermeier, in: Postersession Computerlinguistik Der 40. Jahrestagung Der Deutschen Gesellschaft Für Sprachwissenschaft, 2018.
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[113]
2018 | Conference Paper | LibreCat-ID: 10154
(WIP) Towards the Automated Composition of Machine Learning Services
F. Mohr, M.D. Wever, E. Hüllermeier, A. Faez, in: Proc. 15th Int. Conference on Services Computing (SCC), 2018, pp. 241–244.
LibreCat
 
[112]
2018 | Conference Paper | LibreCat-ID: 10192
ML-Plan for Unlimited-Length Machine Learning Pipelines
M.D. Wever, F. Mohr, E. Hüllermeier, in: Int. Workshop on Automatic Machine Learning (AutoML) at ICML 2018, 2018.
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[111]
2018 | Journal Article | LibreCat-ID: 10274
On the effectiveness of heuristics for learning nested dichotomies: an empirial analysis
V. Melnikov, E. Hüllermeier, Machine Learning 107 (2018) 1537–1560.
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[110]
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.
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[109]
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.
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[108]
2018 | Conference Paper | LibreCat-ID: 2109
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.)
 
[107]
2018 | Conference Paper | LibreCat-ID: 2471
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.)
 
[106]
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
 
[105]
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), 2018, pp. 3469–3477.
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[104]
2018 | Conference Paper | LibreCat-ID: 3552
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.)
 
[103]
2018 | Conference Paper | LibreCat-ID: 10151
Programmatic Task Network Planning
F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proc. 1st ICAPS Workshop on Hierachical  Planning at the 28th Int. Conference on Automated Planning and Scheduling (ICAPS), 2018, pp. 31–39.
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[102]
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.
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[101]
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.
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[100]
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.
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[99]
2018 | Conference Paper | LibreCat-ID: 2857
Programmatic Task Network Planning
F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proceedings of the 28th International Conference on Automated Planning and Scheduling, AAAI, 2018.
LibreCat | Files available | Download (ext.)
 
[98]
2018 | Conference Abstract | LibreCat-ID: 1379
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.)
 
[97]
2018 | Conference Paper | LibreCat-ID: 10152
On-the-Fly Service Construction with Prototypes
F. Mohr, M.D. Wever, E. Hüllermeier, in: Proc. 15th Int. Conference on Services Computing (SCC), 2018, pp. 225–232.
LibreCat
 
[96]
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.
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[95]
2018 | Journal Article | LibreCat-ID: 3510
ML-Plan: Automated Machine Learning via Hierarchical Planning
F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning (2018).
LibreCat | Files available | DOI | Download (ext.)
 
[94]
2018 | Journal Article | LibreCat-ID: 10784
ML-Plan: Automated machine learning via hierarchical planning
F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning 107 (2018) 1495–1515.
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[93]
2018 | Conference Paper | LibreCat-ID: 10188
Ensembles of evolved nested dichotomies for classificaton
M.D. Wever, F. Mohr, E. Hüllermeier, in: Proc. Genetic and Evolutionary Computation Conference (GECCO), 2018, pp. 561–568.
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[92]
2017 | Conference Paper | LibreCat-ID: 1180
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.)
 
[91]
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.
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[90]
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.
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[89]
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.
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[88]
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.
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[87]
2017 | Conference Paper | LibreCat-ID: 10212 LibreCat
 
[86]
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.
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[85]
2017 | Encyclopedia Article | LibreCat-ID: 10589
Preference Learning
J. Fürnkranz, E. Hüllermeier, in: Encyclopedia of Machine Learning and Data Mining, 2017, pp. 1000–1005.
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[84]
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.
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[83]
2017 | Conference Paper | LibreCat-ID: 10206
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.
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[82]
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.
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[81]
2017 | Conference Paper | LibreCat-ID: 10214
Automatic Machine Learning: Hierarchical Planning Versus Evolutionary Optimization
M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 149–166.
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[80]
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.
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[79]
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).
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[78]
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.
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[77]
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.
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[76]
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.
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[75]
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.
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[74]
2016 | Journal Article | LibreCat-ID: 10266 LibreCat
 
[73]
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.
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[72]
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.
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[71]
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.
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[70]
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.
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[69]
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.
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[68]
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.
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[67]
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.
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[66]
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.
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[65]
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.
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[64]
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.
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[63]
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.
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[62]
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
 
[61]
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.
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[60]
2015 | Conference Paper | LibreCat-ID: 10235 LibreCat
 
[59]
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.
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[58]
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.
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[57]
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.
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[56]
2015 | Journal Article | LibreCat-ID: 10320
Does machine learning need fuzzy logic?
E. Hüllermeier, Fuzzy Sets and Systems 281 (2015) 292–299.
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[55]
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.
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[54]
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.
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[53]
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.
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[52]
2015 | Journal Article | LibreCat-ID: 10321 LibreCat
 
[51]
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.
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[50]
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.
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[49]
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.
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[48]
2015 | Journal Article | LibreCat-ID: 10322 LibreCat
 
[47]
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.
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[46]
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.
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[45]
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.
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[44]
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.
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[43]
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.
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[42]
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.
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[41]
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.
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[40]
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.
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[39]
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).
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[38]
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.
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[37]
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.
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[36]
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.
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[35]
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.
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[34]
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.
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[33]
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
 
[32]
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
 
[31]
2014 | Conference Paper | LibreCat-ID: 10249
Mining Rank Data
S. Henzgen, E. Hüllermeier, in: Proceedings Discovery Science, Bled,Slovenia , 2014, pp. 123–134.
LibreCat
 
[30]
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
 
[29]
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
 
[28]
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
 
[27]
2014 | Journal Article | LibreCat-ID: 10308 LibreCat
 
[26]
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
 
[25]
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
 
[24]
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
 
[23]
2014 | Journal Article | LibreCat-ID: 10309 LibreCat
 
[22]
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
 
[21]
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
 
[20]
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
 
[19]
2013 | Conference Paper | LibreCat-ID: 13119
Rule chains for visualizing evolving fuzzy rule-based systems
S. Henzgen, M. Strickert, E. Hüllermeier, in: R. Burduk, K. Jackowski, M. Kurzynski, M. Wozniak, A. Zolnierek (Eds.), In Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, Springer, 2013, pp. 279–288.
LibreCat
 
[18]
2013 | Conference Paper | LibreCat-ID: 13190
Recovery analysis for adaptive learning from non-stationary data streams
A. Shaker, E. Hüllermeier, in: R. Burduk, K. Jackowski, M. Kurzynski, W. Wozniak, A. Zolnierek (Eds.), In Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, Springer, 2013, pp. 289–298.
LibreCat
 
[17]
2013 | Conference Paper | LibreCat-ID: 13115
Learning to rank lexical substitutions
G. Szarvas, R. Busa-Fekete, E. Hüllermeier, in: In Proceedings EMNLP-2013 Conference on Empirical Methods in Natural Language Processing, Seattle, USA, 2013.
LibreCat
 
[16]
2013 | Conference Paper | LibreCat-ID: 13116
Optimizing the F-measure in multi-label classification: Plug-in rule approach versus structured loss minimization
K. Dembczynski, A. Jachnik, W. Kotlowski, W. Waegeman, E. Hüllermeier, in: S. Dasgupta, D. McAllester (Eds.), In Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, 2013, pp. 1130–1138.
LibreCat
 
[15]
2013 | Conference Paper | LibreCat-ID: 13117
Top-k selection based on adaptive sampling of noisy preferences
R. Busa-Fekete, B. Szoreny, P. Weng, W. Cheng, E. Hüllermeier, in: S. Dasgupta, D. McAllester (Eds.), In Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, 2013, pp. 1094–1102.
LibreCat
 
[14]
2013 | Conference Paper | LibreCat-ID: 13118
Preference-based CBR: General ideas and basic principles
E. Hüllermeier, W. Cheng, in: F. Rossi (Ed.), In Proceedings IJCAI-13, 23rd International Joint Conference on Artificial Intelligence, Beijing, China, AAAI Press, 2013, pp. 3012–3016.
LibreCat
 
[13]
2012 | Conference Paper | LibreCat-ID: 13191
Probability estimation for mulit-class classification based on label ranking
W. Cheng, E. Hüllermeier, in: Proceedings ECML/PKDD-2012, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Bristol, UK, 2012.
LibreCat
 
[12]
2012 | Conference Paper | LibreCat-ID: 13192
Consistent multilabel ranking through univariate loss minimization
K. Dembczynski, W. Kotlowski, E. Hüllermeier, in: J. Langford, J. Pineau (Eds.), In Proceedings ICML-2012,  International Conference on Machine Learning, Edinburgh, Scotland, 2012.
LibreCat
 
[11]
2012 | Conference Paper | LibreCat-ID: 13193
An analysis of chaining in multi-label classification
K. Dembczynski, W. Waegeman, E. Hüllermeier, in: In Proceedings ECAI-2012, 20th European Conference on Artificial Inteligence, Montpellier, France , IOS Press, 2012, pp. 294–299.
LibreCat
 
[10]
2012 | Conference Paper | LibreCat-ID: 13120
Label ranking with partial abstention based on thresholded probalistic models
W. Cheng, E. Hüllermeier, W. Waegeman, V. Welker, in: In Proceedings NIPS-2012, 26th Annual Conference on Neural Information Processing Systems, Lake Tahoe, Nevada, USA, 2012.
LibreCat
 
[9]
2011 | Conference Paper | LibreCat-ID: 13195
Preference-based policy iteration: Leveraging preference learning for reinforcement learning
W. Cheng, J. Fuernkranz, E. Hüllermeier, S.H. Park, in: Proceedings ECML/PKDD-2011, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Athens, Greece, , 2011.
LibreCat
 
[8]
2011 | Conference Paper | LibreCat-ID: 13196
Learning from label preferences
J. Fürnkranz, E. Hüllermeier, in: T. Elomaa, J. Hollmen, H. Mannila (Eds.), In Proceedings DS-2011, 14th International  Conference on Discovery Science, Number 6926 in LNAI, Springer, 2011, pp. 2–17.
LibreCat
 
[7]
2011 | Conference Paper | LibreCat-ID: 13588
Bipartite ranking through minimization of univariate loss
W. Kotlowski, K. Dembczynski, E. Hüllermeier, in: In Proceedings ICML-2011, 28th International Conference on Machine Learning, Washington, USA, 2011.
LibreCat
 
[6]
2011 | Conference Paper | LibreCat-ID: 13197
Learning monotone nonlinear models using the Choquet integral
A. Fallah Tehrani, W. Cheng, K. Dembczynski, E. Hüllermeier, in: In Proceedings ECML/PKDD-2011, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Athens, Greece, 2011.
LibreCat
 
[5]
2011 | Conference Paper | LibreCat-ID: 13198
Preference-based CBR: First steps toward a methodological framework
E. Hüllermeier, P. Schlegel, in: A. Ram, N. Wiratunga (Eds.), In Proceedings ICCBR-2011, 19th International Conference on Case-Based Reasoning, Number 6880 in LNAI, Springer, 2011, pp. 77–91.
LibreCat
 
[4]
2011 | Conference Paper | LibreCat-ID: 13194
An exact algorithm for F-measure maximization
K. Dembczynski, W. Waegeman, W. Cheng, E. Hüllermeier, in: In Proceedings NIPS-2011, 25th Annual Conference on Neural Information Processing Systems, Granada, Spain, 2011.
LibreCat
 
[3]
2010 | Conference Paper | LibreCat-ID: 13590
Label ranking based on the Plackett-Luce model
W. Cheng, K. Dembczynski, E. Hüllermeier, in: J. Fürnkranz, T. Joachims (Eds.), In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, 2010, pp. 215–222.
LibreCat
 
[2]
2010 | Conference Paper | LibreCat-ID: 13589
Bayes optimal multilabel classification via probalistic classifier chains
K. Dembczynski, W. Cheng, E. Hüllermeier, in: J. Fürnkranz, T. Joachims (Eds.), In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, 2010, pp. 279–286.
LibreCat
 
[1]
2010 | Conference Paper | LibreCat-ID: 13591
Graded multi-label classification: The ordinal case
W. Cheng, K. Dembczynski, E. Hüllermeier, in: J. Fürnkranz, T. Joachims (Eds.), In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, 2010.
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[122]
2019 | Conference Paper | LibreCat-ID: 10232
Automating Multi-Label Classification Extending ML-Plan
M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.
LibreCat | Files available
 
[121]
2019 | Conference Abstract | LibreCat-ID: 8956
Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking
A. Hetzer, M.D. Wever, F. Mohr, E. Hüllermeier, in: 2019.
LibreCat | Files available
 
[120]
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
 
[119]
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
 
[118]
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
 
[117]
2018 | Conference Paper | LibreCat-ID: 3852
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.)
 
[116]
2018 | Conference Paper | LibreCat-ID: 2479
(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.)
 
[115]
2018 | Conference Paper | LibreCat-ID: 10153
Reduction Stumps for Multi-class Classification
F. Mohr, M.D. Wever, E. Hüllermeier, in: Proc. 17th Int. Symposium on Intelligent Data Analysis (IDA), 2018, pp. 225–237.
LibreCat
 
[114]
2018 | Conference Paper | LibreCat-ID: 10185
Supporting the Cognitive Process in Annotation Tasks
N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M.D. Wever, E. Hüllermeier, in: Postersession Computerlinguistik Der 40. Jahrestagung Der Deutschen Gesellschaft Für Sprachwissenschaft, 2018.
LibreCat
 
[113]
2018 | Conference Paper | LibreCat-ID: 10154
(WIP) Towards the Automated Composition of Machine Learning Services
F. Mohr, M.D. Wever, E. Hüllermeier, A. Faez, in: Proc. 15th Int. Conference on Services Computing (SCC), 2018, pp. 241–244.
LibreCat
 
[112]
2018 | Conference Paper | LibreCat-ID: 10192
ML-Plan for Unlimited-Length Machine Learning Pipelines
M.D. Wever, F. Mohr, E. Hüllermeier, in: Int. Workshop on Automatic Machine Learning (AutoML) at ICML 2018, 2018.
LibreCat
 
[111]
2018 | Journal Article | LibreCat-ID: 10274
On the effectiveness of heuristics for learning nested dichotomies: an empirial analysis
V. Melnikov, E. Hüllermeier, Machine Learning 107 (2018) 1537–1560.
LibreCat
 
[110]
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
 
[109]
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
 
[108]
2018 | Conference Paper | LibreCat-ID: 2109
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.)
 
[107]
2018 | Conference Paper | LibreCat-ID: 2471
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.)
 
[106]
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
 
[105]
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), 2018, pp. 3469–3477.
LibreCat
 
[104]
2018 | Conference Paper | LibreCat-ID: 3552
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.)
 
[103]
2018 | Conference Paper | LibreCat-ID: 10151
Programmatic Task Network Planning
F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proc. 1st ICAPS Workshop on Hierachical  Planning at the 28th Int. Conference on Automated Planning and Scheduling (ICAPS), 2018, pp. 31–39.
LibreCat
 
[102]
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
 
[101]
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
 
[100]
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
 
[99]
2018 | Conference Paper | LibreCat-ID: 2857
Programmatic Task Network Planning
F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proceedings of the 28th International Conference on Automated Planning and Scheduling, AAAI, 2018.
LibreCat | Files available | Download (ext.)
 
[98]
2018 | Conference Abstract | LibreCat-ID: 1379
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.)
 
[97]
2018 | Conference Paper | LibreCat-ID: 10152
On-the-Fly Service Construction with Prototypes
F. Mohr, M.D. Wever, E. Hüllermeier, in: Proc. 15th Int. Conference on Services Computing (SCC), 2018, pp. 225–232.
LibreCat
 
[96]
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
 
[95]
2018 | Journal Article | LibreCat-ID: 3510
ML-Plan: Automated Machine Learning via Hierarchical Planning
F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning (2018).
LibreCat | Files available | DOI | Download (ext.)
 
[94]
2018 | Journal Article | LibreCat-ID: 10784
ML-Plan: Automated machine learning via hierarchical planning
F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning 107 (2018) 1495–1515.
LibreCat
 
[93]
2018 | Conference Paper | LibreCat-ID: 10188
Ensembles of evolved nested dichotomies for classificaton
M.D. Wever, F. Mohr, E. Hüllermeier, in: Proc. Genetic and Evolutionary Computation Conference (GECCO), 2018, pp. 561–568.
LibreCat
 
[92]
2017 | Conference Paper | LibreCat-ID: 1180
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.)
 
[91]
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
 
[90]
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
 
[89]
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
 
[88]
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
 
[87]
2017 | Conference Paper | LibreCat-ID: 10212 LibreCat
 
[86]
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
 
[85]
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
 
[84]
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
 
[83]
2017 | Conference Paper | LibreCat-ID: 10206
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
 
[82]
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
 
[81]
2017 | Conference Paper | LibreCat-ID: 10214
Automatic Machine Learning: Hierarchical Planning Versus Evolutionary Optimization
M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 149–166.
LibreCat
 
[80]
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
 
[79]
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
 
[78]
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
 
[77]
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
 
[76]
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
 
[75]
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
 
[74]
2016 | Journal Article | LibreCat-ID: 10266 LibreCat
 
[73]
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
 
[72]
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
 
[71]
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
 
[70]
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
 
[69]
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
 
[68]
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.
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[67]
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.
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[66]
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.
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[65]
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.
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[64]
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.
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[63]
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.
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[62]
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.
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[61]
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.
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[60]
2015 | Conference Paper | LibreCat-ID: 10235 LibreCat
 
[59]
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.
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[58]
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.
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[57]
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.
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[56]
2015 | Journal Article | LibreCat-ID: 10320
Does machine learning need fuzzy logic?
E. Hüllermeier, Fuzzy Sets and Systems 281 (2015) 292–299.
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[55]
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.
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[54]
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.
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[53]
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.
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[52]
2015 | Journal Article | LibreCat-ID: 10321 LibreCat
 
[51]
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.
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[50]
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.
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[49]
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.
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[48]
2015 | Journal Article | LibreCat-ID: 10322 LibreCat
 
[47]
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.
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[46]
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.
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[45]
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.
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[44]
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.
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[43]
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.
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[42]
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.
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[41]
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.
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[40]
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.
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[39]
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).
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[38]
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.
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[37]
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.
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[36]
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.
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[35]
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.
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[34]
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.
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[33]
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.
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[32]
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.
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[31]
2014 | Conference Paper | LibreCat-ID: 10249
Mining Rank Data
S. Henzgen, E. Hüllermeier, in: Proceedings Discovery Science, Bled,Slovenia , 2014, pp. 123–134.
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[30]
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.
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[29]
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.
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[28]
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.
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[27]
2014 | Journal Article | LibreCat-ID: 10308 LibreCat
 
[26]
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.
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[25]
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.
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[24]
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.
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[23]
2014 | Journal Article | LibreCat-ID: 10309 LibreCat
 
[22]
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.
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[21]
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.
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[20]
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.
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[19]
2013 | Conference Paper | LibreCat-ID: 13119
Rule chains for visualizing evolving fuzzy rule-based systems
S. Henzgen, M. Strickert, E. Hüllermeier, in: R. Burduk, K. Jackowski, M. Kurzynski, M. Wozniak, A. Zolnierek (Eds.), In Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, Springer, 2013, pp. 279–288.
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[18]
2013 | Conference Paper | LibreCat-ID: 13190
Recovery analysis for adaptive learning from non-stationary data streams
A. Shaker, E. Hüllermeier, in: R. Burduk, K. Jackowski, M. Kurzynski, W. Wozniak, A. Zolnierek (Eds.), In Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, Springer, 2013, pp. 289–298.
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[17]
2013 | Conference Paper | LibreCat-ID: 13115
Learning to rank lexical substitutions
G. Szarvas, R. Busa-Fekete, E. Hüllermeier, in: In Proceedings EMNLP-2013 Conference on Empirical Methods in Natural Language Processing, Seattle, USA, 2013.
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[16]
2013 | Conference Paper | LibreCat-ID: 13116
Optimizing the F-measure in multi-label classification: Plug-in rule approach versus structured loss minimization
K. Dembczynski, A. Jachnik, W. Kotlowski, W. Waegeman, E. Hüllermeier, in: S. Dasgupta, D. McAllester (Eds.), In Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, 2013, pp. 1130–1138.
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[15]
2013 | Conference Paper | LibreCat-ID: 13117
Top-k selection based on adaptive sampling of noisy preferences
R. Busa-Fekete, B. Szoreny, P. Weng, W. Cheng, E. Hüllermeier, in: S. Dasgupta, D. McAllester (Eds.), In Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, 2013, pp. 1094–1102.
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[14]
2013 | Conference Paper | LibreCat-ID: 13118
Preference-based CBR: General ideas and basic principles
E. Hüllermeier, W. Cheng, in: F. Rossi (Ed.), In Proceedings IJCAI-13, 23rd International Joint Conference on Artificial Intelligence, Beijing, China, AAAI Press, 2013, pp. 3012–3016.
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[13]
2012 | Conference Paper | LibreCat-ID: 13191
Probability estimation for mulit-class classification based on label ranking
W. Cheng, E. Hüllermeier, in: Proceedings ECML/PKDD-2012, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Bristol, UK, 2012.
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[12]
2012 | Conference Paper | LibreCat-ID: 13192
Consistent multilabel ranking through univariate loss minimization
K. Dembczynski, W. Kotlowski, E. Hüllermeier, in: J. Langford, J. Pineau (Eds.), In Proceedings ICML-2012,  International Conference on Machine Learning, Edinburgh, Scotland, 2012.
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[11]
2012 | Conference Paper | LibreCat-ID: 13193
An analysis of chaining in multi-label classification
K. Dembczynski, W. Waegeman, E. Hüllermeier, in: In Proceedings ECAI-2012, 20th European Conference on Artificial Inteligence, Montpellier, France , IOS Press, 2012, pp. 294–299.
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[10]
2012 | Conference Paper | LibreCat-ID: 13120
Label ranking with partial abstention based on thresholded probalistic models
W. Cheng, E. Hüllermeier, W. Waegeman, V. Welker, in: In Proceedings NIPS-2012, 26th Annual Conference on Neural Information Processing Systems, Lake Tahoe, Nevada, USA, 2012.
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[9]
2011 | Conference Paper | LibreCat-ID: 13195
Preference-based policy iteration: Leveraging preference learning for reinforcement learning
W. Cheng, J. Fuernkranz, E. Hüllermeier, S.H. Park, in: Proceedings ECML/PKDD-2011, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Athens, Greece, , 2011.
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[8]
2011 | Conference Paper | LibreCat-ID: 13196
Learning from label preferences
J. Fürnkranz, E. Hüllermeier, in: T. Elomaa, J. Hollmen, H. Mannila (Eds.), In Proceedings DS-2011, 14th International  Conference on Discovery Science, Number 6926 in LNAI, Springer, 2011, pp. 2–17.
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[7]
2011 | Conference Paper | LibreCat-ID: 13588
Bipartite ranking through minimization of univariate loss
W. Kotlowski, K. Dembczynski, E. Hüllermeier, in: In Proceedings ICML-2011, 28th International Conference on Machine Learning, Washington, USA, 2011.
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[6]
2011 | Conference Paper | LibreCat-ID: 13197
Learning monotone nonlinear models using the Choquet integral
A. Fallah Tehrani, W. Cheng, K. Dembczynski, E. Hüllermeier, in: In Proceedings ECML/PKDD-2011, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Athens, Greece, 2011.
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[5]
2011 | Conference Paper | LibreCat-ID: 13198
Preference-based CBR: First steps toward a methodological framework
E. Hüllermeier, P. Schlegel, in: A. Ram, N. Wiratunga (Eds.), In Proceedings ICCBR-2011, 19th International Conference on Case-Based Reasoning, Number 6880 in LNAI, Springer, 2011, pp. 77–91.
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[4]
2011 | Conference Paper | LibreCat-ID: 13194
An exact algorithm for F-measure maximization
K. Dembczynski, W. Waegeman, W. Cheng, E. Hüllermeier, in: In Proceedings NIPS-2011, 25th Annual Conference on Neural Information Processing Systems, Granada, Spain, 2011.
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[3]
2010 | Conference Paper | LibreCat-ID: 13590
Label ranking based on the Plackett-Luce model
W. Cheng, K. Dembczynski, E. Hüllermeier, in: J. Fürnkranz, T. Joachims (Eds.), In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, 2010, pp. 215–222.
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[2]
2010 | Conference Paper | LibreCat-ID: 13589
Bayes optimal multilabel classification via probalistic classifier chains
K. Dembczynski, W. Cheng, E. Hüllermeier, in: J. Fürnkranz, T. Joachims (Eds.), In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, 2010, pp. 279–286.
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[1]
2010 | Conference Paper | LibreCat-ID: 13591
Graded multi-label classification: The ordinal case
W. Cheng, K. Dembczynski, E. Hüllermeier, in: J. Fürnkranz, T. Joachims (Eds.), In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, 2010.
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