Johannes Fürnkranz

277 papers A* 11A 7B 45C 10Misc 7Journal 99Unranked 66

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dynamic time warping for classifying long-term trends in time series. Data Knowl. Eng. Anna-Christina Glock, Klaus Chmelina, Johannes Fürnkranz, Thomas Hütter
2025	J	`jnl`	Biasing Rule-Based Explanations Towards User Preferences. Inf. Parisa Mahya, Johannes Fürnkranz
2025	—	`conf`	Extraction of Semantically Coherent Rules from Interpretable Models. ICAART (1) Parisa Mahya, Johannes Fürnkranz
2025	B	`conf`	On the Potential of Deep Symbolic Models for Classification Problems. DS Florian Beck, Johannes Fürnkranz, Van Quoc Phuong Huynh
2025	—	`conf`	Partial Pre-Post Code Tree: A Memory-Efficient Tree Structure for Conjunctive Rule Mining. KDD (1) Van Quoc Phuong Huynh, Florian Beck, Johannes Fürnkranz
2025	J	`jnl`	Probabilistic scoring lists for interpretable machine learning. Mach. Learn. Jonas Hanselle, Stefan Heid, Johannes Fürnkranz, Eyke Hüllermeier
2025	—	`conf`	SIEBES: A Case Study in Hallucinatory Hagiography. Challenges and Algorithms for Knowledge Discovery from Data Johannes Fürnkranz
2024	J	`jnl`	Contrastive Learning of Preferences with a Contextual InfoNCE Loss. CoRR Timo Bertram, Johannes Fürnkranz, Martin Müller
2024	B	`conf`	Dynamic Time Warping for Phase Recognition in Tribological Sensor Data. DaWaK Anna-Christina Glock, Johannes Fürnkranz
2024	Misc	`conf`	Efficiently Training Neural Networks for Imperfect Information Games by Sampling Information Sets. KI Timo Bertram, Johannes Fürnkranz, Martin Müller
2024	J	`jnl`	Efficiently Training Neural Networks for Imperfect Information Games by Sampling Information Sets. CoRR Timo Bertram, Johannes Fürnkranz, Martin Müller
2024	J	`jnl`	Explainable and interpretable machine learning and data mining. Data Min. Knowl. Discov. Martin Atzmueller, Johannes Fürnkranz, Tomás Kliegr, Ute Schmid
2024	—	`conf`	Learning Deep Rule Concepts as Alternating Boolean Pattern Trees. DS (2) Florian Beck, Johannes Fürnkranz, Van Quoc Phuong Huynh
2024	C	`conf`	Learning With Generalised Card Representations for "Magic: The Gathering". CoG Timo Bertram, Johannes Fürnkranz, Martin Müller
2024	J	`jnl`	Learning With Generalised Card Representations for "Magic: The Gathering". CoRR Timo Bertram, Johannes Fürnkranz, Martin Müller
2024	J	`jnl`	Learning decision catalogues for situated decision making: The case of scoring systems. Int. J. Approx. Reason. Stefan Heid, Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier
2024	J	`jnl`	Neural Network-Based Information Set Weighting for Playing Reconnaissance Blind Chess. IEEE Trans. Games Timo Bertram, Johannes Fürnkranz, Martin Müller
2024	J	`jnl`	Neural Network-based Information Set Weighting for Playing Reconnaissance Blind Chess. CoRR Timo Bertram, Johannes Fürnkranz, Martin Müller
2024	J	`jnl`	On the efficient implementation of classification rule learning. Adv. Data Anal. Classif. Michael Rapp, Johannes Fürnkranz, Eyke Hüllermeier
2024	J	`jnl`	Predictive change point detection for heterogeneous data. Neural Comput. Appl. Anna-Christina Glock, Florian Sobieczky, Johannes Fürnkranz, Peter Filzmoser, Martin Jech
2024	J	`jnl`	Probabilistic Scoring Lists for Interpretable Machine Learning. CoRR Jonas Hanselle, Stefan Heid, Johannes Fürnkranz, Eyke Hüllermeier
2024	—	`conf`	When Characteristic Rule-based Models Should be Preferred over Discriminative Ones. ITAT Florian Beck, Johannes Fürnkranz, Van Quoc Phuong Huynh
2023	J	`jnl`	Efficient learning of large sets of locally optimal classification rules. CoRR Van Quoc Phuong Huynh, Johannes Fürnkranz, Florian Beck
2023	J	`jnl`	Efficient learning of large sets of locally optimal classification rules. Mach. Learn. Van Quoc Phuong Huynh, Johannes Fürnkranz, Florian Beck
2023	—	`conf`	Generalizing Conjunctive and Disjunctive Rule Learning to Learning m-of-n Concepts. ITAT Florian Beck, Johannes Fürnkranz, Van Quoc Phuong Huynh
2023	B	`conf`	Layerwise Learning of Mixed Conjunctive and Disjunctive Rule Sets. RuleML+RR Florian Beck, Johannes Fürnkranz, Van Quoc Phuong Huynh
2023	J	`jnl`	Predictive change point detection for heterogeneous data. CoRR Anna-Christina Glock, Florian Sobieczky, Johannes Fürnkranz, Peter Filzmoser, Martin Jech
2023	B	`conf`	Probabilistic Scoring Lists for Interpretable Machine Learning. DS Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier
2023	J	`jnl`	Tree-based dynamic classifier chains. Mach. Learn. Eneldo Loza Mencía, Moritz Kulessa, Simon Bohlender, Johannes Fürnkranz
2023	C	`conf`	Weighting Information Sets with Siamese Neural Networks in Reconnaissance Blind Chess. CoG Timo Bertram, Johannes Fürnkranz, Martin Müller
2022	J	`jnl`	A flexible class of dependence-aware multi-label loss functions. Mach. Learn. Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencía, Johannes Fürnkranz, Michael Rapp
2022	J	`jnl`	Comparing Boosting and Bagging for Decision Trees of Rankings. J. Classif. Antonella Plaia, Simona Buscemi, Johannes Fürnkranz, Eneldo Loza Mencía
2022	J	`jnl`	GausSetExpander: A Simple Approach for Entity Set Expansion. CoRR Aïssatou Diallo, Johannes Fürnkranz
2022	B	`conf`	Incremental Update of Locally Optimal Classification Rules. DS Van Quoc Phuong Huynh, Florian Beck, Johannes Fürnkranz
2022	—	`conf`	On the Incremental Construction of Deep Rule Theories. ITAT Florian Beck, Johannes Fürnkranz, Van Quoc Phuong Huynh
2022	J	`jnl`	Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability. CoRR Timo Bertram, Johannes Fürnkranz, Martin Müller
2022	C	`conf`	Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess. CoG Timo Bertram, Johannes Fürnkranz, Martin Müller
2022	J	`jnl`	Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess. CoRR Timo Bertram, Johannes Fürnkranz, Martin Müller
2022	—	`conf`	Towards Deep and Interpretable Rule Learning (invited paper). ITAT Johannes Fürnkranz
2022	Misc	`conf`	Unsupervised Alignment of Distributional Word Embeddings. KI Aïssatou Diallo, Johannes Fürnkranz
2021	J	`jnl`	A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems. CoRR Timo Bertram, Johannes Fürnkranz, Martin Müller
2021	J	`jnl`	A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance. Comput. Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
2021	J	`jnl`	A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. Artif. Intell. Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
2021	J	`jnl`	An Empirical Investigation Into Deep and Shallow Rule Learning. Frontiers Artif. Intell. Florian Beck, Johannes Fürnkranz
2021	J	`jnl`	An Empirical Investigation into Deep and Shallow Rule Learning. CoRR Florian Beck, Johannes Fürnkranz
2021	J	`jnl`	An Investigation into Mini-Batch Rule Learning. CoRR Florian Beck, Johannes Fürnkranz
2021	—	`conf`	Beyond DNF: First Steps towards Deep Rule Learning. ITAT Florian Beck, Johannes Fürnkranz
2021	J	`jnl`	Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance. Frontiers Big Data Michael Rapp, Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
2021	J	`jnl`	Correlation-based Discovery of Disease Patterns for Syndromic Surveillance. CoRR Michael Rapp, Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
2021	B	`conf`	Elliptical Ordinal Embedding. DS Aïssatou Diallo, Johannes Fürnkranz
2021	J	`jnl`	Elliptical Ordinal Embedding. CoRR Aïssatou Diallo, Johannes Fürnkranz
2021	—	`conf`	Gradient-Based Label Binning in Multi-label Classification. ECML/PKDD (3) Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier
2021	J	`jnl`	Gradient-based Label Binning in Multi-label Classification. CoRR Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier
2021	J	`jnl`	Learning Ordinal Embedding from Sets. Entropy Aïssatou Diallo, Johannes Fürnkranz
2021	J	`jnl`	Ordinal Monte Carlo Tree Search. CoRR Tobias Joppen, Johannes Fürnkranz
2021	C	`conf`	Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking. CoG Timo Bertram, Johannes Fürnkranz, Martin Müller
2021	J	`jnl`	Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking. CoRR Timo Bertram, Johannes Fürnkranz, Martin Müller
2021	J	`jnl`	Revisiting Non-Specific Syndromic Surveillance. CoRR Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
2021	B	`conf`	Revisiting Non-specific Syndromic Surveillance. IDA Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
2021	C	`conf`	Some Chess-Specific Improvements for Perturbation-Based Saliency Maps. CoG Jessica Fritz, Johannes Fürnkranz
2021	B	`conf`	Structuring Rule Sets Using Binary Decision Diagrams. RuleML+RR Florian Beck, Johannes Fürnkranz, Van Quoc Phuong Huynh
2021	B	`conf`	Sum-Product Networks for Early Outbreak Detection of Emerging Diseases. AIME Moritz Kulessa, Bennet Wittelsbach, Eneldo Loza Mencía, Johannes Fürnkranz
2021	—	`conf`	The Machine Reconnaissance Blind Chess Tournament of NeurIPS 2022. NeurIPS (Competition and Demos) Ryan W. Gardner, Gino Perrotta, Anvay Shah, Shivaram Kalyanakrishnan, Kevin A. Wang, Gregory Clark, Timo Bertram, Johannes Fürnkranz, Martin Müller, Brady P. Garrison, Prithviraj Dasgupta, Saeid Rezaei
2021	J	`jnl`	Tree-Based Dynamic Classifier Chains. CoRR Eneldo Loza Mencía, Moritz Kulessa, Simon Bohlender, Johannes Fürnkranz
2020	J	`jnl`	A Flexible Class of Dependence-aware Multi-Label Loss Functions. CoRR Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencía, Johannes Fürnkranz, Michael Rapp
2020	Misc	`conf`	Conformal Rule-Based Multi-label Classification. KI Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía
2020	J	`jnl`	Conformal Rule-Based Multi-label Classification. CoRR Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía
2020	—	`conf`	Learning Gradient Boosted Multi-label Classification Rules. ECML/PKDD (3) Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
2020	J	`jnl`	Learning Gradient Boosted Multi-label Classification Rules. CoRR Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
2020	J	`jnl`	Learning Structured Declarative Rule Sets - A Challenge for Deep Discrete Learning. CoRR Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía, Michael Rapp
2020	J	`jnl`	Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data. Frontiers Artif. Intell. Johannes Czech, Moritz Willig, Alena Beyer, Kristian Kersting, Johannes Fürnkranz
2020	B	`conf`	On Aggregation in Ensembles of Multilabel Classifiers. DS Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2020	J	`jnl`	On Aggregation in Ensembles of Multilabel Classifiers. CoRR Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2020	J	`jnl`	On cognitive preferences and the plausibility of rule-based models. Mach. Learn. Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim
2020	—	`conf`	Ordinal Monte Carlo Tree Search. MCS@IJCAI Tobias Joppen, Johannes Fürnkranz
2020	A	`conf`	Permutation Learning via Lehmer Codes. ECAI Aïssatou Diallo, Markus Zopf, Johannes Fürnkranz
2020	B	`conf`	Rule-Based Multi-label Classification: Challenges and Opportunities. RuleML+RR Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, Vu-Linh Nguyen, Michael Rapp
2020	—	`ch.`	Vertrauenswürdiges, transparentes und robustesMaschinelles Lernen. Handbuch der Künstlichen Intelligenz Christian Bauckhage, Johannes Fürnkranz, Gerhard Paaß
2019	J	`jnl`	Advances in Machine Learning for the Behavioral Sciences. CoRR Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
2019	B	`conf`	Beta Distribution Drift Detection for Adaptive Classifiers. ESANN Lukas Fleckenstein, Sebastian Kauschke, Johannes Fürnkranz
2019	—	`conf`	Deep Ordinal Reinforcement Learning. ECML/PKDD (3) Alexander Zap, Tobias Joppen, Johannes Fürnkranz
2019	J	`jnl`	Deep Ordinal Reinforcement Learning. CoRR Alexander Zap, Tobias Joppen, Johannes Fürnkranz
2019	C	`conf`	Driver Information Embedding with Siamese LSTM networks. IV Hien Q. Dang, Johannes Fürnkranz
2019	—	`conf`	Improving Answer Selection with Analogy-Preserving Sentence Embeddings. LWDA Aïssatou Diallo, Markus Zopf, Johannes Fürnkranz
2019	J	`jnl`	Improving Outbreak Detection with Stacking of Statistical Surveillance Methods. CoRR Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
2019	—	`conf`	Improving the Fusion of Outbreak Detection Methods with Supervised Learning. CIBB Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
2019	B	`conf`	Learning Analogy-Preserving Sentence Embeddings for Answer Selection. CoNLL Aïssatou Diallo, Markus Zopf, Johannes Fürnkranz
2019	J	`jnl`	Learning Analogy-Preserving Sentence Embeddings for Answer Selection. CoRR Aïssatou Diallo, Markus Zopf, Johannes Fürnkranz
2019	A*	`conf`	Learning Context-dependent Label Permutations for Multi-label Classification. ICML Jinseok Nam, Young-Bum Kim, Eneldo Loza Mencía, Sunghyun Park, Ruhi Sarikaya, Johannes Fürnkranz
2019	J	`jnl`	Learning to play the Chess Variant Crazyhouse above World Champion Level with Deep Neural Networks and Human Data. CoRR Johannes Czech, Moritz Willig, Alena Beyer, Kristian Kersting, Johannes Fürnkranz
2019	B	`conf`	Mending is Better than Ending: Adapting Immutable Classifiers to Nonstationary Environments using Ensembles of Patches. IJCNN Sebastian Kauschke, Lukas Fleckenstein, Johannes Fürnkranz
2019	B	`conf`	On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics. DS Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2019	J	`jnl`	On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics. CoRR Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2019	C	`conf`	Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation. CoG Tobias Joppen, Tilman Strübig, Johannes Fürnkranz
2019	J	`jnl`	Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation. CoRR Tobias Joppen, Tilman Strübig, Johannes Fürnkranz
2019	J	`jnl`	Ordinal Monte Carlo Tree Search. CoRR Tobias Joppen, Johannes Fürnkranz
2019	B	`conf`	Patching Deep Neural Networks for Nonstationary Environments. IJCNN Sebastian Kauschke, David Hermann Lehmann, Johannes Fürnkranz
2019	Misc	`conf`	Personalized Transaction Kernels for Recommendation Using MCTS. KI Maryam Tavakol, Tobias Joppen, Ulf Brefeld, Johannes Fürnkranz
2019	J	`jnl`	Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy. CoRR Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2019	J	`jnl`	The PRORETA 4 City Assistant System. Autom. Julian Schwehr, Stefan Luthardt, Hien Q. Dang, Maren Henzel, Hermann Winner, Jürgen Adamy, Johannes Fürnkranz, Volker Willert, Benedikt Lattke, Maximilian Höpfl, Christoph Wannemacher
2018	J	`jnl`	A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. CoRR Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
2018	A*	`conf`	Batchwise Patching of Classifiers. AAAI Sebastian Kauschke, Johannes Fürnkranz
2018	J	`jnl`	Beta Distribution Drift Detection for Adaptive Classifiers. CoRR Lukas Fleckenstein, Sebastian Kauschke, Johannes Fürnkranz
2018	—	`conf`	Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules. PAKDD (1) Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2018	J	`jnl`	Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules. CoRR Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2018	—	`conf`	Exploiting Maneuver Dependency for Personalization of a Driver Model. LWDA Hien Q. Dang, Johannes Fürnkranz
2018	J	`jnl`	Informed Hybrid Game Tree Search for General Video Game Playing. IEEE Trans. Games Tobias Joppen, Miriam Ulrike Moneke, Nils Schröder, Christian Wirth, Johannes Fürnkranz
2018	J	`jnl`	Learning Interpretable Rules for Multi-label Classification. CoRR Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier, Michael Rapp
2018	B	`conf`	Leveraging Reproduction-Error Representations for Multi-Instance Classification. DS Sebastian Kauschke, Max Mühlhäuser, Johannes Fürnkranz
2018	J	`jnl`	On Cognitive Preferences and the Interpretability of Rule-based Models. CoRR Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim
2018	Misc	`conf`	Preference-Based Monte Carlo Tree Search. KI Tobias Joppen, Christian Wirth, Johannes Fürnkranz
2018	J	`jnl`	Preference-Based Monte Carlo Tree Search. CoRR Tobias Joppen, Christian Wirth, Johannes Fürnkranz
2018	B	`conf`	The Need for Interpretability Biases. IDA Johannes Fürnkranz, Tomás Kliegr
2018	C	`conf`	Towards Semi-Supervised Classification of Event Streams via Denoising Autoencoders. ICMLA Sebastian Kauschke, Max Mühlhäuser, Johannes Fürnkranz
2018	—	`conf`	Using Past Maneuver Executions for Personalization of a Driver Model. ITSC Hien Q. Dang, Johannes Fürnkranz
2018	—	`conf`	What's Important in a Text? An Extensive Evaluation of Linguistic Annotations for Summarization. SNAMS Markus Zopf, Teresa Botschen, Tobias Falke, Benjamin Heinzerling, Ana Marasovic, Todor Mihaylov, Avinesh P. V. S., Eneldo Loza Mencía, Johannes Fürnkranz, Anette Frank
2018	—	`conf`	Which Scores to Predict in Sentence Regression for Text Summarization? NAACL-HLT Markus Zopf, Eneldo Loza Mencía, Johannes Fürnkranz
2017	J	`jnl`	A Survey of Preference-Based Reinforcement Learning Methods. J. Mach. Learn. Res. Christian Wirth, Riad Akrour, Gerhard Neumann, Johannes Fürnkranz
2017	—	`ch.`	Class Binarization. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Classification Rule. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Covering Algorithm. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Decision List. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Decision Lists and Decision Trees. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Decision Stump. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Decision Tree. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Divide-and-Conquer Learning. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	B	`conf`	Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression. DS Andrei Tolstikov, Frederik Janssen, Johannes Fürnkranz
2017	—	`conf`	Interactive Data Analytics for the Humanities. CICLing (1) Iryna Gurevych, Christian M. Meyer, Carsten Binnig, Johannes Fürnkranz, Kristian Kersting, Stefan Roth, Edwin Simpson
2017	Misc	`ed.`	KI 2017: Advances in Artificial Intelligence - 40th Annual German Conference on AI, Dortmund, Germany, September 25-29, 2017, Proceedings KI Gabriele Kern-Isberner, Johannes Fürnkranz, Matthias Thimm
2017	—	`ch.`	Machine Learning and Game Playing. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`conf`	Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification. NIPS Jinseok Nam, Eneldo Loza Mencía, Hyunwoo J. Kim, Johannes Fürnkranz
2017	C	`conf`	Multi-objective Optimisation-Based Feature Selection for Multi-label Classification. NLDB Mohammed Arif Khan, Asif Ekbal, Eneldo Loza Mencía, Johannes Fürnkranz
2017	—	`ch.`	Preference Learning. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz, Eyke Hüllermeier
2017	—	`ch.`	Pruning. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Rank Correlation. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz, Eyke Hüllermeier
2017	B	`conf`	Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction. DS Camila González, Eneldo Loza Mencía, Johannes Fürnkranz
2017	J	`jnl`	Refinement and selection heuristics in subgroup discovery and classification rule learning. Expert Syst. Appl. Anita Valmarska, Nada Lavrac, Johannes Fürnkranz, Marko Robnik-Sikonja
2017	—	`ch.`	Rule Learning. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`ch.`	Rule Set. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz
2017	—	`conf`	Time-to-lane-change prediction with deep learning. ITSC Hien Q. Dang, Johannes Fürnkranz, Alexander Biedermann, Maximilian Höpfl
2016	A*	`conf`	All-in Text: Learning Document, Label, and Word Representations Jointly. AAAI Jinseok Nam, Eneldo Loza Mencía, Johannes Fürnkranz
2016	B	`conf`	Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization. CoNLL Markus Zopf, Eneldo Loza Mencía, Johannes Fürnkranz
2016	A*	`conf`	Model-Free Preference-Based Reinforcement Learning. AAAI Christian Wirth, Johannes Fürnkranz, Gerhard Neumann
2016	B	`conf`	Predicting Cargo Train Failures: A Machine Learning Approach for a Lightweight Prototype. DS Sebastian Kauschke, Johannes Fürnkranz, Frederik Janssen
2016	B	`conf`	Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization. COLING Markus Zopf, Eneldo Loza Mencía, Johannes Fürnkranz
2016	B	`conf`	Shorter Rules Are Better, Aren't They? DS Julius Stecher, Frederik Janssen, Johannes Fürnkranz
2016	J	`jnl`	Special Issue on Discovery Science. Inf. Sci. Johannes Fürnkranz, Eyke Hüllermeier
2016	B	`conf`	Using semantic similarity for multi-label zero-shot classification of text documents. ESANN Prateek Veeranna Sappadla, Jinseok Nam, Eneldo Loza Mencía, Johannes Fürnkranz
2016	B	`conf`	What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation. COLING Fabian Hirschmann, Jinseok Nam, Johannes Fürnkranz
2015	—	`conf`	A Brief Overview of Rule Learning. RuleML Johannes Fürnkranz, Tomás Kliegr
2015	J	`jnl`	Editorial. Data Min. Knowl. Discov. Johannes Fürnkranz
2015	A	`conf`	Event-Based Clustering for Reducing Labeling Costs of Event-related Microposts. ICWSM Axel Schulz, Frederik Janssen, Petar Ristoski, Johannes Fürnkranz
2015	—	`conf`	Event-based Clustering for Reducing Labeling Costs of Incident-Related Microposts. MUD@ICML Axel Schulz, Petar Ristoski, Johannes Fürnkranz, Frederik Janssen
2015	J	`jnl`	On Learning From Game Annotations. IEEE Trans. Comput. Intell. AI Games Christian Wirth, Johannes Fürnkranz
2015	—	`conf`	On the Importance of a Hierarchy for Learning Continuous Vector Representations of a Label Space. ICLR (Workshop) Jinseok Nam, Johannes Fürnkranz
2015	—	`conf`	Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning. ECML/PKDD (1) Jinseok Nam, Eneldo Loza Mencía, Hyunwoo J. Kim, Johannes Fürnkranz
2014	J	`jnl`	Efficient implementation of class-based decomposition schemes for Naïve Bayes. Mach. Learn. Sang-Hyeun Park, Johannes Fürnkranz
2014	A*	`conf`	Graded Multilabel Classification by Pairwise Comparisons. ICDM Christian Brinker, Eneldo Loza Mencía, Johannes Fürnkranz
2014	—	`conf`	Knowledge Discovery in Scientific Literature. KONVENS Jinseok Nam, Christian Kirschner, Zheng Ma, Nicolai Erbs, Susanne Neumann, Daniela Oelke, Steffen Remus, Chris Biemann, Judith Eckle-Kohler, Johannes Fürnkranz, Iryna Gurevych, Marc Rittberger, Karsten Weihe
2014	—	`conf`	Large-Scale Multi-label Text Classification - Revisiting Neural Networks. ECML/PKDD (2) Jinseok Nam, Jungi Kim, Eneldo Loza Mencía, Iryna Gurevych, Johannes Fürnkranz
2014	J	`jnl`	Preference Learning (Dagstuhl Seminar 14101). Dagstuhl Reports Johannes Fürnkranz, Eyke Hüllermeier, Cynthia Rudin, Roman Slowinski, Scott Sanner
2014	—	`conf`	Preference Learning from Annotated Game Databases. LWA Christian Wirth, Johannes Fürnkranz
2014	—	`conf`	Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning. ECML/PKDD (3) Julius Stecher, Frederik Janssen, Johannes Fürnkranz
2013	B	`conf`	A Policy Iteration Algorithm for Learning from Preference-Based Feedback. IDA Christian Wirth, Johannes Fürnkranz
2013	B	`ed.`	Discovery Science - 16th International Conference, DS 2013, Singapore, October 6-9, 2013. Proceedings Discovery Science Johannes Fürnkranz, Eyke Hüllermeier, Tomoyuki Higuchi
2013	C	`conf`	EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning. ACML Christian Wirth, Johannes Fürnkranz
2013	J	`jnl`	Editorial: Preference learning and ranking. Mach. Learn. Eyke Hüllermeier, Johannes Fürnkranz
2013	J	`jnl`	Large-scale Multi-label Text Classification - Revisiting Neural Networks. CoRR Jinseok Nam, Jungi Kim, Iryna Gurevych, Johannes Fürnkranz
2012	J	`jnl`	Efficient prediction algorithms for binary decomposition techniques. Data Min. Knowl. Discov. Sang-Hyeun Park, Johannes Fürnkranz
2012	B	`conf`	Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction. Discovery Science Johannes Fürnkranz, Sang-Hyeun Park
2012	—	`book`	Foundations of Rule Learning Johannes Fürnkranz, Dragan Gamberger, Nada Lavrac
2012	B	`conf`	Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns. IDA Wouter Duivesteijn, Eneldo Loza Mencía, Johannes Fürnkranz, Arno J. Knobbe
2012	J	`jnl`	Preference-based reinforcement learning: a formal framework and a policy iteration algorithm. Mach. Learn. Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park
2012	—	`conf`	Unsupervised generation of data mining features from linked open data. WIMS Heiko Paulheim, Johannes Fürnkranz
2011	J	`jnl`	A review and comparison of strategies for handling missing values in separate-and-conquer rule learning. J. Intell. Inf. Syst. Lars Wohlrab, Johannes Fürnkranz
2011	A*	`conf`	Heuristic Rule-Based Regression via Dynamic Reduction to Classification. IJCAI Frederik Janssen, Johannes Fürnkranz
2011	—	`conf`	Heuristic Rule-Based Regression via Dynamic Reduction to Classification. LWA Frederik Janssen, Johannes Fürnkranz
2011	B	`conf`	Learning from Label Preferences. ALT Eyke Hüllermeier, Johannes Fürnkranz
2011	B	`conf`	Learning from Label Preferences. Discovery Science Eyke Hüllermeier, Johannes Fürnkranz
2011	—	`conf`	Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning. ECML/PKDD (1) Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park
2011	B	`conf`	Rule Stacking: An Approach for Compressing an Ensemble of Rule Sets into a Single Classifier. Discovery Science Jan-Nikolas Sulzmann, Johannes Fürnkranz
2010	—	`ch.`	Decision List. Encyclopedia of Machine Learning Johannes Fürnkranz
2010	—	`ch.`	Decision Lists and Decision Trees. Encyclopedia of Machine Learning Johannes Fürnkranz
2010	—	`ch.`	Decision Tree. Encyclopedia of Machine Learning Johannes Fürnkranz
2010	—	`conf`	Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. Semantic Processing of Legal Texts Eneldo Loza Mencía, Johannes Fürnkranz
2010	J	`jnl`	Efficient voting prediction for pairwise multilabel classification. Neurocomputing Eneldo Loza Mencía, Sang-Hyeun Park, Johannes Fürnkranz
2010	—	`ch.`	Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms. Advances in Machine Learning I Nada Lavrac, Johannes Fürnkranz, Dragan Gamberger
2010	B	`conf`	Exploiting Code Redundancies in ECOC. Discovery Science Sang-Hyeun Park, Lorenz Weizsäcker, Johannes Fürnkranz
2010	J	`jnl`	Guest Editorial: Global modeling using local patterns. Data Min. Knowl. Discov. Johannes Fürnkranz, Arno J. Knobbe
2010	J	`jnl`	Learning to Recognize Missing E-Mail Attachments. Appl. Artif. Intell. Marco Ghiglieri, Johannes Fürnkranz
2010	—	`ch.`	Machine Learning and Game Playing. Encyclopedia of Machine Learning Johannes Fürnkranz
2010	J	`jnl`	On exploiting hierarchical label structure with pairwise classifiers. SIGKDD Explor. Johannes Fürnkranz, Jan Frederik Sima
2010	J	`jnl`	On predictive accuracy and risk minimization in pairwise label ranking. J. Comput. Syst. Sci. Eyke Hüllermeier, Johannes Fürnkranz
2010	J	`jnl`	On the quest for optimal rule learning heuristics. Mach. Learn. Frederik Janssen, Johannes Fürnkranz
2010	—	`ch.`	Preference Learning and Ranking by Pairwise Comparison. Preference Learning Johannes Fürnkranz, Eyke Hüllermeier
2010	—	`book`	Preference Learning. Johannes Fürnkranz, Eyke Hüllermeier
2010	—	`ch.`	Preference Learning. Encyclopedia of Machine Learning Johannes Fürnkranz, Eyke Hüllermeier
2010	—	`ch.`	Preference Learning: An Introduction. Preference Learning Johannes Fürnkranz, Eyke Hüllermeier
2010	—	`conf`	Probability Estimation and Aggregation for Rule Learning. LWA Jan-Nikolas Sulzmann, Johannes Fürnkranz
2010	A*	`ed.`	Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel ICML Johannes Fürnkranz, Thorsten Joachims
2010	—	`ch.`	Pruning. Encyclopedia of Machine Learning Johannes Fürnkranz
2010	—	`ch.`	Rule Learning. Encyclopedia of Machine Learning Johannes Fürnkranz
2010	—	`conf`	Separate-and-conquer Regression. LWA Frederik Janssen, Johannes Fürnkranz
2010	—	`ch.`	Web Mining. Data Mining and Knowledge Discovery Handbook Johannes Fürnkranz
2009	A	`conf`	A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. SDM Frederik Janssen, Johannes Fürnkranz
2009	B	`conf`	An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules. Discovery Science Jan-Nikolas Sulzmann, Johannes Fürnkranz
2009	Misc	`conf`	An Exploitative Monte-Carlo Poker Agent. KI Immanuel Schweizer, Kamill Panitzek, Sang-Hyeun Park, Johannes Fürnkranz
2009	—	`conf`	An Exploitative Monte-Carlo Poker Agent. LWA Immanuel Schweizer, Kamill Panitzek, Sang-Hyeun Park, Johannes Fürnkranz
2009	—	`conf`	Binary Decomposition Methods for Multipartite Ranking. ECML/PKDD (1) Johannes Fürnkranz, Eyke Hüllermeier, Stijn Vanderlooy
2009	—	`conf`	Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification. ECML/PKDD (2) Sang-Hyeun Park, Johannes Fürnkranz
2009	—	`conf`	Efficient Voting Prediction for Pairwise Multilabel Classification. LWA Eneldo Loza Mencía, Sang-Hyeun Park, Johannes Fürnkranz
2009	B	`conf`	Efficient voting prediction for pairwise multilabel classification. ESANN Eneldo Loza Mencía, Sang-Hyeun Park, Johannes Fürnkranz
2009	—	`conf`	On Table Extraction from Text Sources with Markups. LWA Lorenz Weizsäcker, Johannes Fürnkranz
2008	—	`conf`	A Comparison of Techniques for Selecting and Combining Class Association Rules. LWA Jan-Nikolas Sulzmann, Johannes Fürnkranz
2008	—	`conf`	A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. LWA Frederik Janssen, Johannes Fürnkranz
2008	B	`conf`	An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics. Discovery Science Frederik Janssen, Johannes Fürnkranz
2008	—	`conf`	Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain. ECML/PKDD (2) Eneldo Loza Mencía, Johannes Fürnkranz
2008	B	`conf`	Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach. PRICAI Dragan Gamberger, Nada Lavrac, Johannes Fürnkranz
2008	J	`jnl`	Label ranking by learning pairwise preferences. Artif. Intell. Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng, Klaus Brinker
2008	J	`jnl`	Learning the Piece Values for Three Chess Variants. ICGA J. Sacha Droste, Johannes Fürnkranz
2008	J	`jnl`	Multilabel classification via calibrated label ranking. Mach. Learn. Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía, Klaus Brinker
2008	B	`conf`	Pairwise learning of multilabel classifications with perceptrons. IJCNN Eneldo Loza Mencía, Johannes Fürnkranz
2007	—	`conf`	An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. LWA Eneldo Loza Mencía, Johannes Fürnkranz
2007	—	`conf`	Efficient Pairwise Classification. ECML Sang-Hyeun Park, Johannes Fürnkranz
2007	—	`conf`	Meta-Learning Rule Learning Heuristics. LWA Frederik Janssen, Johannes Fürnkranz
2007	A*	`conf`	On Meta-Learning Rule Learning Heuristics. ICDM Frederik Janssen, Johannes Fürnkranz
2007	—	`conf`	On Minimizing the Position Error in Label Ranking. ECML Eyke Hüllermeier, Johannes Fürnkranz
2007	—	`conf`	On Pairwise Naive Bayes Classifiers. ECML Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyke Hüllermeier
2006	A	`conf`	A Unified Model for Multilabel Classification and Ranking. ECAI Klaus Brinker, Johannes Fürnkranz, Eyke Hüllermeier
2006	—	`ed.`	Knowledge Discovery in Databases: PKDD 2006, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings PKDD Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou
2006	—	`ed.`	Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings ECML Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou
2006	J	`jnl`	Machine learning and games. Mach. Learn. Michael H. Bowling, Johannes Fürnkranz, Thore Graepel, Ron Musick
2006	—	`conf`	On Trading Off Consistency and Coverage in Inductive Rule Learning. LWA Frederik Janssen, Johannes Fürnkranz
2005	B	`conf`	Learning Label Preferences: Ranking Error Versus Position Error. IDA Eyke Hüllermeier, Johannes Fürnkranz
2005	—	`ed.`	Lernen, Wissensentdeckung und Adaptivität (LWA) 2005, GI Workshops, Saarbrücken, October 10th-12th, 2005 LWA Mathias Bauer, Boris Brandherm, Johannes Fürnkranz, Gunter Grieser, Andreas Hotho, Andreas Jedlitschka, Alexander Kröner
2005	—	`conf`	Link-Local Features for Hypertext Classification. EWMF/KDO Hervé Utard, Johannes Fürnkranz
2005	—	`conf`	On Position Error and Label Ranking through Iterated Choice. LWA Eyke Hüllermeier, Johannes Fürnkranz, Jürgen Beringer
2005	J	`jnl`	Preference Learning. Künstliche Intell. Johannes Fürnkranz, Eyke Hüllermeier
2005	J	`jnl`	ROC 'n' Rule Learning - Towards a Better Understanding of Covering Algorithms. Mach. Learn. Johannes Fürnkranz, Peter A. Flach
2005	—	`ch.`	Web Mining. The Data Mining and Knowledge Discovery Handbook Johannes Fürnkranz
2004	—	`conf`	An Analysis of Stopping and Filtering Criteria for Rule Learning. ECML Johannes Fürnkranz, Peter A. Flach
2004	—	`conf`	From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms. Local Pattern Detection Johannes Fürnkranz
2004	—	`conf`	Modeling Rule Precision. LWA Johannes Fürnkranz
2004	B	`conf`	Ranking by pairwise comparison a note on risk minimization. FUZZ-IEEE Eyke Hüllermeier, Johannes Fürnkranz
2003	A*	`conf`	An Analysis of Rule Evaluation Metrics. ICML Johannes Fürnkranz, Peter A. Flach
2003	B	`conf`	Combining Pairwise Classifiers with Stacking. IDA Petr Savický, Johannes Fürnkranz
2003	—	`conf`	Pairwise Preference Learning and Ranking. ECML Johannes Fürnkranz, Eyke Hüllermeier
2003	J	`jnl`	Round robin ensembles. Intell. Data Anal. Johannes Fürnkranz
2002	B	`conf`	A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning. ALT Johannes Fürnkranz
2002	J	`jnl`	Hyperlink ensembles: a case study in hypertext classification. Inf. Fusion Johannes Fürnkranz
2002	—	`conf`	Pairwise Classification as an Ensemble Technique. ECML Johannes Fürnkranz
2002	J	`jnl`	Round Robin Classification. J. Mach. Learn. Res. Johannes Fürnkranz
2002	J	`jnl`	User Profiling for the MELVIL Knowledge Retrieval System. Appl. Artif. Intell. Johannes Fürnkranz, Christian Holzbaur, Robert Temel
2001	B	`conf`	An Evaluation of Grading Classifiers. IDA Alexander K. Seewald, Johannes Fürnkranz
2001	—	`conf`	Detecting Temporal Change in Event Sequences: An Application to Demographic Data. PKDD Hendrik Blockeel, Johannes Fürnkranz, Alexia Prskawetz, Francesco C. Billari
2001	A*	`conf`	Round Robin Rule Learning. ICML Johannes Fürnkranz
2000	A	`conf`	Learning to Use Operational Advice. ECAI Johannes Fürnkranz, Bernhard Pfahringer, Hermann Kaindl, Stefan Kramer
2000	J	`jnl`	Searching for Patterns in Political Event Sequences: Experiments with the Keds Database. Cybern. Syst. Klaus Kovar, Johannes Fürnkranz, Johann Petrak, Bernhard Pfahringer, Robert Trappl, Gerhard Widmer
1999	B	`conf`	Exploiting Structural Information for Text Classification on the WWW. IDA Johannes Fürnkranz
1999	J	`jnl`	Report on the Machine-Learning in Game-Playing Workshop. ICCA J. Johannes Fürnkranz, Moroslaw Kubat
1999	J	`jnl`	Separate-and-Conquer Rule Learning. Artif. Intell. Rev. Johannes Fürnkranz
1998	J	`jnl`	A Hypothesis on the Divergence of AI Research. ICCA J. Franz-Günter Winkler, Johannes Fürnkranz
1998	J	`jnl`	Guest Editorial: First-Order Knowledge Discovery in Databases. Appl. Artif. Intell. Johannes Fürnkranz, Bernhard Pfahringer
1998	J	`jnl`	Integrative Windowing CoRR Johannes Fürnkranz
1998	J	`jnl`	Integrative Windowing. J. Artif. Intell. Res. Johannes Fürnkranz
1997	J	`jnl`	Knowledge Discovery in International Conflict Databases. Appl. Artif. Intell. Johannes Fürnkranz, Johann Petrak, Robert Trappl
1997	—	`conf`	More Efficient Windowing. AAAI/IAAI Johannes Fürnkranz
1997	—	`conf`	Noise-Tolerant Windowing. IJCAI (2) Johannes Fürnkranz
1997	—	`conf`	On Effort in AI Research: A Description Along Two Dimensions. Deep Blue Versus Kasparov: The Significance for Artificial Intelligence Franz-Günter Winkler, Johannes Fürnkranz
1997	J	`jnl`	Pruning Algorithms for Rule Learning. Mach. Learn. Johannes Fürnkranz
1996	A	`conf`	Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases. ECAI Robert Trappl, Johannes Fürnkranz, Johann Petrak
1996	J	`jnl`	Machine Learning in Computer Chess: The Next Generation. ICCA J. Johannes Fürnkranz
1995	—	`conf`	A Tight Integration of Pruning and Learning (Extended Abstract). ECML Johannes Fürnkranz
1994	—	`conf`	A Comparison of Pruning Methods for Relational Concept Learning. KDD Workshop Johannes Fürnkranz
1994	—	`conf`	FOSSIL: A Robust Relational Learner. ECML Johannes Fürnkranz
1994	A*	`conf`	Incremental Reduced Error Pruning. ICML Johannes Fürnkranz, Gerhard Widmer
1994	A	`conf`	Top-Down Pruning in Relational Learning. ECAI Johannes Fürnkranz