TY - CONF AU - Jasinska, K. AU - Dembczynski, K. AU - Busa-Fekete, Robert AU - Klerx, Timo AU - Hüllermeier, Eyke ED - Balcan, M.F. ED - Weinberger, K.Q. ID - 10222 T2 - Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA TI - Extreme F-measure maximization using sparse probability estimates ER - TY - CONF AU - Melnikov, Vitaly AU - Hüllermeier, Eyke ID - 10223 T2 - European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy TI - Learning to aggregate using uninorms, in Proceedings ECML/PKDD-2016 ER - TY - CONF AU - Dembczynski, K. AU - Kotlowski, W. AU - Waegeman, W. AU - Busa-Fekete, Robert AU - Hüllermeier, Eyke ID - 10224 T2 - In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy TI - Consistency of probalistic classifier trees ER - TY - CONF AU - Shabani, Aulon AU - Paul, Adil AU - Platon, R. AU - Hüllermeier, Eyke ID - 10225 T2 - In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA TI - Predicting the electricity consumption of buildings: An improved CBR approach ER - TY - CONF AU - Pfannschmidt, Karlson AU - Hüllermeier, Eyke AU - Held, S. AU - Neiger, R. ID - 10226 T2 - In Proceedings IPMU 16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands TI - Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical concepts ER - TY - CONF AU - Labreuche, C. AU - Hüllermeier, Eyke AU - Vojtas, P. AU - Fallah Tehrani, A. ED - Busa-Fekete, Robert ED - Hüllermeier, Eyke ED - Mousseau, V. ED - Pfannschmidt, Karlson ID - 10227 T2 - Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning TI - On the Identifiability of models in multi-criteria preference learning ER - TY - CONF AU - Schäfer, Dirk AU - Hüllermeier, Eyke ED - Busa-Fekete, Robert ED - Hüllermeier, Eyke ED - Mousseau, V. ED - Pfannschmidt, Karlson ID - 10228 T2 - Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning TI - Preference-Based Reinforcement Learning Using Dyad Ranking ER - TY - CONF AU - Couso, Ines AU - Ahmadi Fahandar, Mohsen AU - Hüllermeier, Eyke ED - Busa-Fekete, Robert ED - Hüllermeier, Eyke ED - Mousseau, V. ED - Pfannschmidt, Karlson ID - 10229 T2 - Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning TI - Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators ER - TY - CONF AU - Lu, S. AU - Hüllermeier, Eyke ED - Hoffmann, F. ED - Hüllermeier, Eyke ED - Mikut, R. ID - 10230 T2 - Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing TI - Support vector classification on noisy data using fuzzy supersets losses ER - TY - CONF AU - Schäfer, Dirk AU - Hüllermeier, Eyke ID - 10231 T2 - In Workshop LWDA "Lernen, Wissen, Daten, Analysen" TI - Plackett-Luce networks for dyad ranking ER - TY - GEN ED - Kaminka, G.A. ED - Fox, M. ED - Bouquet, P. ED - Hüllermeier, Eyke ED - Dignum, V. ED - Dignum, F. ED - van Harmelen, F. ID - 10263 TI - ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial Intelligence VL - 285 ER - TY - JOUR AU - Leinweber, M. AU - Fober, T. AU - Strickert, M. AU - Baumgärtner, L. AU - Klebe, G. AU - Freisleben, B. AU - Hüllermeier, Eyke ID - 10264 IS - 6 JF - IEEE Transactions on Knowledge and Data Engineering TI - CavSimBase: A database for large scale comparison of protein binding sites VL - 28 ER - TY - JOUR AU - Riemenschneider, M. AU - Senge, Robin AU - Neumann, U. AU - Hüllermeier, Eyke AU - Heider, D. ID - 10266 IS - 10 JF - BioData Mining TI - Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification VL - 9 ER - TY - CONF AB - The Collaborative Research Centre "On-The-Fly Computing" works on foundations and principles for the vision of the Future Internet. It proposes the paradigm of On-The-Fly Computing, which tackles emerging worldwide service markets. In these markets, service providers trade software, platform, and infrastructure as a service. Service requesters state requirements on services. To satisfy these requirements, the new role of brokers, who are (human) actors building service compositions on the fly, is introduced. Brokers have to specify service compositions formally and comprehensively using a domain-specific language (DSL), and to use service matching for the discovery of the constituent services available in the market. The broker's choice of the DSL and matching approaches influences her success of building compositions as distinctive properties of different service markets play a significant role. In this paper, we propose a new approach of engineering a situation-specific DSL by customizing a comprehensive, modular DSL and its matching for given service market properties. This enables the broker to create market-specific composition specifications and to perform market-specific service matching. As a result, the broker builds service compositions satisfying the requester's requirements more accurately. We evaluated the presented concepts using case studies in service markets for tourism and university management. AU - Arifulina, Svetlana AU - Platenius, Marie Christin AU - Mohr, Felix AU - Engels, Gregor AU - Schäfer, Wilhelm ID - 280 T2 - Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet TI - Market-Specific Service Compositions: Specification and Matching ER - TY - JOUR AB - On-the-fly composition of service-based software solutions is still a challenging task. Even more challenges emerge when facing automatic service composition in markets of composed services for end users. In this paper, we focus on the functional discrepancy between “what a user wants” specified in terms of a request and “what a user gets” when executing a composed service. To meet the challenge of functional discrepancy, we propose the combination of existing symbolic composition approaches with machine learning techniques. We developed a learning recommendation system that expands the capabilities of existing composition algorithms to facilitate adaptivity and consequently reduces functional discrepancy. As a representative of symbolic techniques, an Artificial Intelligence planning based approach produces solutions that are correct with respect to formal specifications. Our learning recommendation system supports the symbolic approach in decision-making. Reinforcement Learning techniques enable the recommendation system to adjust its recommendation strategy over time based on user ratings. We implemented the proposed functionality in terms of a prototypical composition framework. Preliminary results from experiments conducted in the image processing domain illustrate the benefit of combining both complementary techniques. AU - Jungmann, Alexander AU - Mohr, Felix ID - 323 IS - 1 JF - Journal of Internet Services and Applications TI - An approach towards adaptive service composition in markets of composed services ER - TY - CONF AB - Services are self-contained software components that can beused platform independent and that aim at maximizing software reuse. Abasic concern in service oriented architectures is to measure the reusabilityof services. One of the most important qualities is the functionalreusability, which indicates how relevant the task is that a service solves.Current metrics for functional reusability of software, however, have verylittle explanatory power and do not accomplish this goal.This paper presents a new approach to estimate the functional reusabilityof services based on their relevance. To this end, it denes the degreeto which a service enables the execution of other services as its contri-bution. Based on the contribution, relevance of services is dened as anestimation for their functional reusability. Explanatory power is obtainedby normalizing relevance values with a reference service. The applicationof the metric to a service test set conrms its supposed capabilities. AU - Mohr, Felix ID - 324 T2 - Proceedings of the 14th International Conference on Software Reuse (ICSR) TI - A Metric for Functional Reusability of Services ER - TY - CONF AB - Services are self-contained and platform independent software components that aim at maximizing software reuse. The automated composition of services to a target software artifact has been tackled with many AI techniques, but existing approaches make unreasonably strong assumptions such as a predefined data flow, are limited to tiny problem sizes, ignore non-functional properties, or assume offline service repositories. This paper presents an algorithm that automatically composes services without making such assumptions. We employ a backward search algorithm that starts from an empty composition and prepends service calls to already discovered candidates until a solution is found. Available services are determined during the search process. We implemented our algorithm, performed an experimental evaluation, and compared it to other approaches. AU - Mohr, Felix AU - Jungmann, Alexander AU - Kleine Büning, Hans ID - 319 T2 - Proceedings of the 12th IEEE International Conference on Services Computing (SCC) TI - Automated Online Service Composition ER - TY - JOUR AU - Senge, Robin AU - Hüllermeier, Eyke ID - 4792 IS - 6 JF - IEEE Transactions on Fuzzy Systems SN - 1063-6706 TI - Fast Fuzzy Pattern Tree Learning for Classification VL - 23 ER - TY - CONF AU - Schäfer, D. AU - Hüllermeier, Eyke ID - 15406 T2 - in Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm Selection co-located ECML/PKDD, Porto, Portugal TI - Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations ER - TY - CONF AU - Paul, Adil AU - Hüllermeier, Eyke ID - 15749 T2 - In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany TI - A cbr approach to the angry birds game ER - TY - CONF AU - Ewerth, R. AU - Balz, A. AU - Gehlhaar, J. AU - Dembczynski, K. AU - Hüllermeier, Eyke ED - Hoffmann, F. ED - Hüllermeier, Eyke ID - 15750 T2 - In Proceedings 25. Workshop Computational Intelligence, Dortmund, Germany TI - Depth estimation in monocular images: Quantitative versus qualitative approaches ER - TY - CONF AU - Lu, S. AU - Hüllermeier, Eyke ED - Hoffmann, F. ED - Hüllermeier, Eyke ID - 15751 T2 - in Proceedings 25th Workshop Computational Intelligence, Dortmund Germany TI - Locally weighted regression through data imprecisiation ER - TY - JOUR AU - Senge, Robin AU - Hüllermeier, Eyke ID - 16049 IS - 6 JF - IEEE Transactions on Fuzzy Systems TI - Fast fuzzy pattern tree learning for classification VL - 23 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 16051 IS - 6 JF - Informatik Spektrum TI - From knowledge-based to data driven fuzzy modeling: Development, criticism and alternative directions VL - 38 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 16053 JF - Fuzzy Sets and Systems TI - Does machine learning need fuzzy logic? VL - 281 ER - TY - JOUR AU - Waegeman, W. AU - Dembczynski, K. AU - Jachnik, A. AU - Cheng, W. AU - Hüllermeier, Eyke ID - 16058 JF - Journal of Machine Learning Research TI - On the Bayes-optimality of F-measure maximizers VL - 15 ER - TY - JOUR AU - Shaker, A. AU - Hüllermeier, Eyke ID - 16067 JF - Neurocomputing TI - Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study VL - 150 ER - TY - CONF AU - Hüllermeier, Eyke AU - Minor, M. ID - 10234 T2 - in Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015) LNAI 9343 TI - Case-Based Reasoning Research and Development ER - TY - CONF AU - Hoffmann, F. AU - Hüllermeier, Eyke ID - 10235 TI - Proceedings 25. Workshop Computational Intelligence KIT Scientific Publishing ER - TY - CONF AU - Abdel-Aziz, A. AU - Hüllermeier, Eyke ID - 10236 T2 - In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015) TI - Case Base Maintenance in Preference-Based CBR ER - TY - CONF AU - Szörényi, B. AU - Busa-Fekete, Robert AU - Weng, P. AU - Hüllermeier, Eyke ID - 10237 T2 - In Proceedings International Conference on Machine Learning (ICML 2015) TI - Qualitative Multi-Armed Bandits: A Quantile-Based Approach ER - TY - CONF AU - Schäfer, Dirk AU - Hüllermeier, Eyke ID - 10238 T2 - in Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD) TI - Dyad Ranking Using A Bilinear Plackett-Luce Model ER - TY - CONF AU - Hüllermeier, Eyke AU - Cheng, W. ID - 10239 T2 - in Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD) TI - Superset Learning Based on Generalized Loss Minimization ER - TY - CONF AU - Henzgen, Sascha AU - Hüllermeier, Eyke ID - 10240 T2 - in Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD) TI - Weighted Rank Correlation : A Flexible Approach Based on Fuzzy Order Relations ER - TY - CONF AU - Szörényi, B. AU - Busa-Fekete, Robert AU - Paul, Adil AU - Hüllermeier, Eyke ID - 10241 T2 - in Advances in Neural Information Processing Systems 28 (NIPS 2015) TI - Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach ER - TY - CONF AU - Szörényi, B. AU - Busa-Fekete, Robert AU - Dembczynski, K. AU - Hüllermeier, Eyke ID - 10242 T2 - in Advances in Neural Information Processing Systems 28 (NIPS 2015) TI - Online F-Measure Optimization ER - TY - CONF AU - El Mesaoudi-Paul, Adil AU - Hüllermeier, Eyke ID - 10243 T2 - in Workshop Proc. 23rd International Conference on Case-Based Reasoning (ICCBR 2015) TI - A CBR Approach to the Angry Birds Game ER - TY - CONF AU - Schäfer, Dirk AU - Hüllermeier, Eyke ID - 10244 T2 - in Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel@PKDD/ECML) TI - Preference-Based Meta- Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations ER - TY - CONF AU - Lu, S. AU - Hüllermeier, Eyke ID - 10245 T2 - Proceedings 25. Workshop Computational Intelligence TI - Locally weighted regression through data imprecisiation ER - TY - CONF AU - Ewerth, Ralph AU - Balz, A. AU - Gehlhaar, J. AU - Dembczynski, K. AU - Hüllermeier, Eyke ID - 10246 T2 - Proceedings 25. Workshop Computational Intelligence TI - Depth estimation in monocular images: Quantitative versus qualitative approaches ER - TY - JOUR AU - Waegeman, W. AU - Dembczynski, K. AU - Jachnik, A. AU - Cheng, W. AU - Hüllermeier, Eyke ID - 10319 JF - in Journal of Machine Learning Research TI - On the Bayes-Optimality of F-Measure Maximizers VL - 15 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 10320 JF - Fuzzy Sets and Systems TI - Does machine learning need fuzzy logic? VL - 281 ER - TY - JOUR AU - Shaker, Ammar AU - Hüllermeier, Eyke ID - 10321 JF - Neurocomputing TI - Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study VL - 150 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 10322 IS - 6 JF - Informatik Spektrum TI - From Knowledge-based to Data-driven fuzzy modeling-Development, criticism and alternative directions VL - 38 ER - TY - JOUR AU - Garcia-Jimenez, S. AU - Bustince, U. AU - Hüllermeier, Eyke AU - Mesiar, R. AU - Pal, N.R. AU - Pradera, A. ID - 10323 IS - 4 JF - IEEE Transactions on Fuzzy Systems TI - Overlap Indices: Construction of and Application of Interpolative Fuzzy Systems VL - 23 ER - TY - JOUR AU - Senge, Robin AU - Hüllermeier, Eyke ID - 10324 IS - 6 JF - IEEE Transactions on Fuzzy Systems TI - Fast Fuzzy Pattern Tree Learning of Classification VL - 23 ER - TY - JOUR AU - Basavaraju, Manu AU - Chandran, L Sunil AU - Rajendraprasad, Deepak AU - Ramaswamy, Arunselvan ID - 24155 IS - 6 JF - Graphs and Combinatorics TI - Rainbow connection number of graph power and graph products VL - 30 ER - TY - JOUR AU - Basavaraju, Manu AU - Chandran, L Sunil AU - Rajendraprasad, Deepak AU - Ramaswamy, Arunselvan ID - 24156 IS - 2 JF - Graphs and Combinatorics TI - Rainbow connection number and radius VL - 30 ER - TY - CONF AB - There are many technologies for the automation of processesthat deal with services; examples are service discovery and composition.Automation of these processes requires that the services are described semantically. However, semantically described services are currently not oronly rarely available, which limits the applicability of discovery and composition approaches. The systematic support for creating new semanticservices usable by automated technologies is an open problem.We tackle this problem with a template based approach: Domain independent templates are instantiated with domain specific services andboolean expressions. The obtained services have semantic descriptionswhose correctness directly follows from the correctness of the template.Besides the theory, we present experimental results for a service repository in which 85% of the services were generated automatically. AU - Mohr, Felix AU - Walther, Sven ID - 353 T2 - Proceedings of the 14th International Conference on Software Reuse (ICSR) TI - Template-based Generation of Semantic Services ER - TY - CONF AB - Automatic service composition is still a challengingtask. It is even more challenging when dealing witha dynamic market of services for end users. New servicesmay enter the market while other services are completelyremoved. Furthermore, end users are typically no experts in thedomain in which they formulate a request. As a consequence,ambiguous user requests will inevitably emerge and have tobe taken into account. To meet these challenges, we proposea new approach that combines automatic service compositionwith adaptive service recommendation. A best first backwardsearch algorithm produces solutions that are functional correctwith respect to user requests. An adaptive recommendationsystem supports the search algorithm in decision-making.Reinforcement Learning techniques enable the system to adjustits recommendation strategy over time based on user ratings.The integrated approach is described on a conceptional leveland demonstrated by means of an illustrative example fromthe image processing domain. AU - Jungmann, Alexander AU - Mohr, Felix AU - Kleinjohann, Bernd ID - 447 T2 - Proceedings of the 10th World Congress on Services (SERVICES) TI - Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services ER - TY - CONF AB - Automatically composing service-based software solutionsis still a challenging task. Functional as well as nonfunctionalproperties have to be considered in order to satisfyindividual user requests. Regarding non-functional properties,the composition process can be modeled as optimization problemand solved accordingly. Functional properties, in turn, can bedescribed by means of a formal specification language. Statespacebased planning approaches can then be applied to solvethe underlying composition problem. However, depending on theexpressiveness of the applied formalism and the completenessof the functional descriptions, formally equivalent services maystill differ with respect to their implemented functionality. As aconsequence, the most appropriate solution for a desired functionalitycan hardly be determined without considering additionalinformation. In this paper, we demonstrate how to overcome thislack of information by means of Reinforcement Learning. Inorder to resolve ambiguity, we expand state-space based servicecomposition by a recommendation mechanism that supportsdecision-making beyond formal specifications. The recommendationmechanism adjusts its recommendation strategy basedon feedback from previous composition runs. Image processingserves as case study. Experimental results show the benefit of ourproposed solution. AU - Jungmann, Alexander AU - Mohr, Felix AU - Kleinjohann, Bernd ID - 457 T2 - Proceedings of the 7th International Conference on Service Oriented Computing and Applications (SOCA) TI - Applying Reinforcement Learning for Resolving Ambiguity in Service Composition ER - TY - CONF AB - Services are self-contained software components that can be used platform independent and that aim at maximizing software reuse. A basic concern in service oriented architectures is to measure the reusability of services. One of the most important qualities is the functional reusability, which indicates how relevant the task is that a service solves. Current metrics for functional reusability of software, however, either require source code analysis or have very little explanatory power. This paper gives a formally described vision statement for the estimation of functional reusability of services and sketches an exemplary reusability metric that is based on the service descriptions. AU - Mohr, Felix ID - 428 T2 - Proceedings of the 12th International Conference on Service Oriented Computing (ICSOC) TI - Estimating Functional Reusability of Services ER - TY - JOUR AU - Agarwal, M. AU - Fallah Tehrani, A. AU - Hüllermeier, Eyke ID - 16046 IS - 3-4 JF - Journal of Multi-Criteria Decision Analysis TI - Preference-based learning of ideal solutions in TOPSIS-like decision models VL - 22 ER - TY - JOUR AU - Krotzky, T. AU - Fober, T. AU - Hüllermeier, Eyke AU - Klebe, G. ID - 16060 IS - 5 JF - IEEE/ACM Transactions of Computational Biology and Bioinformatics TI - Extended graph-based models for enhanced similarity search in Cabase VL - 11 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 16064 IS - 7 JF - International Journal of Approximate Reasoning TI - Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization VL - 55 ER - TY - JOUR AU - Henzgen, Sascha AU - Strickert, M. AU - Hüllermeier, Eyke ID - 16069 JF - Evolving Systems TI - Visualization of evolving fuzzy-rule-based systems VL - 5 ER - TY - JOUR AU - Busa-Fekete, Robert AU - Szörenyi, B. AU - Weng, P. AU - Cheng, W. AU - Hüllermeier, Eyke ID - 16077 IS - 3 JF - Machine Learning TI - Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm. VL - 97 ER - TY - JOUR AU - Krempl, G. AU - Zliobaite, I. AU - Brzezinski, D. AU - Hüllermeier, Eyke AU - Last, M. AU - Lemaire, V. AU - Noack, T. AU - Shaker, A. AU - Sievi, S. AU - Spiliopoulou, M. AU - Stefanowski, J. ID - 16078 IS - 1 JF - SIGKDD Explorations TI - Open challenges for data stream mining research VL - 16 ER - TY - JOUR AU - Strickert, M. AU - Bunte, K. AU - Schleif, F.M. AU - Hüllermeier, Eyke ID - 16079 JF - Neurocomputing TI - Correlation-based embedding of pairwise score data VL - 141 ER - TY - JOUR AU - Shaker, Ammar AU - Hüllermeier, Eyke ID - 16080 IS - 1 JF - International Journal of Applied Mathematics and Computer Science TI - Survival analysis on data streams: Analyzing temporal events in dynamically changing environments VL - 24 ER - TY - JOUR AU - Senge, Robin AU - Bösner, S. AU - Dembczynski, K. AU - Haasenritter, J. AU - Hirsch, O. AU - Donner-Banzhoff, N. AU - Hüllermeier, Eyke ID - 16082 JF - Information Sciences TI - Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty VL - 255 ER - TY - JOUR AU - Donner-Banzhoff, N. AU - Haasenritter, J. AU - Hüllermeier, Eyke AU - Viniol, A. AU - Bösner, S. AU - Becker, A. ID - 16083 IS - 67 JF - Journal of Clinical Epidemiology TI - The comprehensive diagnostic study is suggested as a design to model the diagnostic process VL - 2 ER - TY - CONF AU - Busa-Fekete, Robert AU - Szörényi, B. AU - Hüllermeier, Eyke ID - 10247 T2 - Proceedings AAAI 2014, Quebec, Canada TI - PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences ER - TY - CONF AU - Busa-Fekete, Robert AU - Hüllermeier, Eyke ID - 10248 T2 - Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia TI - A Survey of Preference-Based Online Learning with Bandit Algorithms ER - TY - CONF AU - Henzgen, Sascha AU - Hüllermeier, Eyke ID - 10249 T2 - Proceedings Discovery Science, Bled,Slovenia TI - Mining Rank Data ER - TY - CONF AU - Fallah Tehrani, A. AU - Strickert, M. AU - Hüllermeier, Eyke ID - 10250 T2 - Proceedings ESANN , Bruges, Belgium TI - The Choquet kernel for monotone data ER - TY - CONF AU - Abdel-Aziz, A. AU - Strickert, M. AU - Hüllermeier, Eyke ID - 10251 T2 - Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland TI - Learning Solution Similarity in Preference-Based CBR ER - TY - CONF AU - Schäfer, Dirk AU - Hüllermeier, Eyke ID - 10253 T2 - Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany TI - Dyad Ranking Using A Bilinear Plackett-Luce Model ER - TY - CONF AU - Calders, T. AU - Esposito, F. AU - Hüllermeier, Eyke AU - Meo, R. ID - 10254 T2 - Proceedings, Parts I-III. Lecture Notes in Computer Science TI - Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France ER - TY - CONF AU - Fürnkranz, J. AU - Hüllermeier, Eyke AU - Rudin, Cynthia AU - Slowinski, Roman AU - Sanner, Scott ID - 10295 IS - 3 TI - Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports VL - 4 ER - TY - JOUR AU - Shaker, Ammar AU - Hüllermeier, Eyke ID - 10296 IS - 1 JF - Applied Mathematics and Computer Science TI - Survival analysis on data streams: Analyzing temporal events in dynamically changing environments VL - 24 ER - TY - JOUR AU - Hoffmann, F. AU - Hüllermeier, Eyke AU - Kroll, A. ID - 10297 IS - 10 JF - Computational Intelligence Automatisierungstechnik TI - Ausgewählte Beiträge des GMA-Fachausschusses 5.14 VL - 62 ER - TY - JOUR AU - Calders, T. AU - Esposito, F. AU - Hüllermeier, Eyke AU - Meo, R. ID - 10298 IS - 5-6 JF - Data Min. Knowledge Discovery TI - Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track VL - 28 ER - TY - JOUR AU - Henzgen, Sascha AU - Strickert, M. AU - Hüllermeier, Eyke ID - 10299 IS - 3 JF - Evolving Systems TI - Visualization of evolving fuzzy rule-based systems VL - 5 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 10308 IS - 7 JF - Int. J. Approx. Reasoning TI - Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization VL - 55 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 10309 IS - 7 JF - Int. J. Approx. Reasoning TI - Rejoinder on "Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization VL - 55 ER - TY - JOUR AU - Strickert, M. AU - Bunte, K. AU - Schleif, F.- M. AU - Hüllermeier, Eyke ID - 10310 JF - Neurocomputing TI - Correlation-based embedding of pairwise score data VL - 141 ER - TY - JOUR AU - Senge, Robin AU - Bösner, S. AU - Dembczynski, K. AU - Haasenritter, J. AU - Hirsch, O. AU - Donner-Banzhoff, N. AU - Hüllermeier, Eyke ID - 10311 JF - Information Sciences TI - Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty VL - 255 ER - TY - JOUR AU - Mernberger, M. AU - Moog, M. AU - Stork, S. AU - Zauner, S. AU - Maier, U.G. AU - Hüllermeier, Eyke ID - 10312 IS - 1 JF - J. Bioinformatics and Computational Biology TI - Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances VL - 12 ER - TY - JOUR AU - Calders, T. AU - Esposito, F. AU - Hüllermeier, Eyke AU - Meo, R. ID - 10313 IS - 1-2 JF - Machine Learning TI - Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track VL - 97 ER - TY - JOUR AU - Busa-Fekete, Robert AU - Szörényi, B. AU - Weng, P. AU - Cheng, W. AU - Hüllermeier, Eyke ID - 10314 IS - 3 JF - Machine Learning TI - Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm VL - 97 ER - TY - JOUR AU - Montanés, E. AU - Senge, Robin AU - Barranquero, J. AU - Quevedo, J.R. AU - Del Coz, J.J. AU - Hüllermeier, Eyke ID - 10315 IS - 3 JF - Pattern Recognition TI - Dependent binary relevance models for multi-label classification VL - 47 ER - TY - JOUR AU - Krempl, G. AU - Zliobaite, I. AU - Brzezinski, D. AU - Hüllermeier, Eyke AU - Last, M. AU - Lemaire, V. AU - Noack, T. AU - Shaker, Ammar AU - Sievi, S. AU - Spiliopoulou, M. AU - Stefanowski, J. ID - 10316 IS - 1 JF - SIGKDD Explorations TI - Open challenges for data stream mining research VL - 16 ER - TY - JOUR AU - Krotzky, T. AU - Fober, T. AU - Hüllermeier, Eyke AU - Klebe, G. ID - 10317 IS - 5 JF - IEEE/ACM Trans. Comput. Biology Bioinform. TI - Extended Graph-Based Models for Enhanced Similarity Search in Cavbase VL - 11 ER - TY - JOUR AU - Stock, M. AU - Fober, T. AU - Hüllermeier, Eyke AU - Glinca, S, AU - Klebe, G. AU - Pahikkala, T. AU - Airola, A. AU - De Baets, B. AU - Wageman, W. ID - 10318 IS - 6 JF - IEEE/ACM Trans. Comput. Biology Bioinform. TI - Identification of Functionally Releated Enzymes by Learning to Rank Methods VL - 11 ER - TY - CONF AB - Software composition has been studied as a subject of state based planning for decades. Existing composition approaches that are efficient enough to be used in practice are limited to sequential arrangements of software components. This restriction dramatically reduces the number of composition problems that can be solved. However, there are many composition problems that could be solved by existing approaches if they had a possibility to combine components in very simple non-sequential ways. To this end, we present an approach that arranges not only basic components but also composite components. Composite components enhance the structure of the composition by conditional control flows. Through algorithms that are written by experts, composite components are automatically generated before the composition process starts. Therefore, our approach is not a substitute for existing composition algorithms but complements them with a preprocessing step. We verified the validity of our approach through implementation of the presented algorithms. AU - Mohr, Felix AU - Kleine Büning, Hans ID - 485 T2 - Proceedings of the 15th International Conference on Information Integration and Web-based Applications & Services (iiWAS) TI - Semi-Automated Software Composition Through Generated Components ER - TY - CONF AB - Automated service composition has been studied as a subject of state based planning for a decade. A great deal of service composition tasks can only be solved if concrete output values of the services are considered in the composition process. However, the fact that those values are not known before runtime leads to nondeterministic planning problems, which have proven to be notoriously difficult in practical automated service composition applications. Even though this problem is frequently recognized, it has still received remarkably few attention and remains unsolved.This paper shows how nondeterminism in automated service composition can be reduced. We introduce context rules as a means to derive semantic knowledge from output values of services. These rules enable us to replace nondeterministic composition operations by less nondeterministic or even completely deterministic ones. We show the validity of our solutions not only theoretically but also have evaluated them practically through implementation. AU - Mohr, Felix AU - Lettmann, Theodor AU - Kleine Büning, Hans ID - 495 T2 - Proceedings of the 6th International Conference on Service Oriented Computing and Applications (SOCA) TI - Reducing Nondeterminism in Automated Service Composition ER - TY - CONF AU - Cheng, W. AU - Henzgen, S. AU - Hüllermeier, Eyke ID - 15752 T2 - In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Bamberg, Germany TI - Labelwise versus pairwise decomposition in label ranking ER - TY - CONF AU - Senge, Robin AU - del Coz, J. AU - Hüllermeier, Eyke ID - 15753 T2 - In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Bamberg, Germany TI - Rectifying classifier chains for multi-label classification, Bamberg, Germany ER - TY - CONF AU - Busa-Fekete, Robert AU - Fober, T. AU - Hüllermeier, Eyke ED - Hoffmann, F. ED - Hüllermeier, Eyke ID - 15755 T2 - in Proceedings 23th Workshop Computational Intelligence, Dortmund Germany TI - Preference-based evolutionary optimization using generalized racing algorithms ER - TY - CONF AU - Henzgen, S. AU - Hüllermeier, Eyke ED - Hoffmann, F. ED - Hüllermeier, Eyke ID - 15756 T2 - in Proceedings 23th Workshop Computational Intelligence, Dortmund Germany TI - Weighted rank correlation measures based on fuzzy order relations ER - TY - CONF AU - Weng, P. AU - Busa-Fekete, Robert AU - Hüllermeier, Eyke ID - 15757 T2 - In Proceedings ECML/PKDD-Workshop on Reinforcement learning from Generalized Feedback:Beyond Numerical Rewards, Prague TI - Interactive Q-learning with ordinal rewards and unreliable tutor ER - TY - CONF AU - Busa-Fekete, Robert AU - Szörenyi, B. AU - Weng, P. AU - Hüllermeier, Eyke ID - 15758 T2 - In Proceedings ECML/PKDD-Workshop on Reinforcement learning from Generalized Feedback:Beyond Numerical Rewards, Prague TI - Preference-based evolutionary direct policy search ER - TY - CONF AU - Cheng, W. AU - Hüllermeier, Eyke ID - 15759 T2 - In Proceedings M-PREF`13, 7th Multidisciplinary Workshop on Advances in Preference Handling Beijing, China TI - A nearest neigbor approach to label ranking based on generalized labelwise loss minimization ER - TY - CONF AU - Shaker, Ammar AU - Hüllermeier, Eyke ED - Krempl, G. ED - Zliobaite, I. ED - Wang, Y. ED - Forman, G. ID - 15760 T2 - In Proceedings RealStream 2013, 1st International Workshop on Real-World Challenges for Data Stream Mining, Prague, Czech Republic TI - Event history analysis on data streams: An application to earthquake occurence ER - TY - CONF AU - Senge, Robin AU - del Coz, J.J. AU - Hüllermeier, Eyke ED - Schmidt-Thieme, L. ED - Spiliopoulou, M. ID - 15761 T2 - In Proceedings of GFKL-2012, 36th Annual Conference of the German Classification Society, Studies in Classification, Data Analysis and Knowledge Organization, Hildesheim, Germany TI - On the problem of error propagation in classier chains for multi-label classification. Data Analysis, Machine Learning and Knowledge Discovery ER - TY - CONF AU - Fober, T. AU - Klebe, G. AU - Hüllermeier, Eyke ED - Lausen, B. ED - Van den Poel, D. ED - Ultsch, A. ID - 15763 T2 - In Proceedings GFKL-2011, Conference of the German Classification Society, Frankfurt Germany TI - Local clique merging: An extension of the maximum common subgraph measure with applications in structural bioinformatics, Algorithms from and for Nature and Life ER - TY - CONF AU - Fallah Tehrani, A. AU - Hüllermeier, Eyke ED - Montero, J. ED - Pasi, G. ED - Ciucci, D. ID - 15112 T2 - in Proceedings EUSFLAT-2013 8th International Conference on the European Society for Fuzzy Logic and Technology, Milano, Italy TI - Ordinal Choquistic regression ER - TY - CONF AU - Nasiri, N. AU - Fober, T. AU - Senge, Robin AU - Hüllermeier, Eyke ID - 15113 T2 - in Proceedings IFSA-2013 World Congress of the International Fuzzy Systems Association, Edmonton, Canada TI - Fuzzy Pattern Trees as an alternative to rule-based fuzzy systems: Knowledge-driven, data-driven and hybrid modeling of colour yield in poyester dyeing, Edmonton, Canada ER - TY - JOUR AU - Heider, D. AU - Senge, Robin AU - Cheng, W. AU - Hüllermeier, Eyke ID - 16044 IS - 16 JF - Bioinformatics TI - Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistence prediction VL - 29 ER -