Johannes Fürnkranz

ORCID

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 117

Top Venues

CoRR

CoG

Mach. Learn.

Publications

Timo Bertram, Johannes Fürnkranz, Martin Müller
Neural Network-based Information Set Weighting for Playing Reconnaissance Blind Chess. CoRR (2024)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Contrastive Learning of Preferences with a Contextual InfoNCE Loss. CoRR (2024)
Stefan Heid, Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier
Learning decision catalogues for situated decision making: The case of scoring systems. Int. J. Approx. Reason. 171 (2024)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Learning With Generalised Card Representations for "Magic: The Gathering". CoRR (2024)
Anna-Christina Glock, Johannes Fürnkranz
Dynamic Time Warping for Phase Recognition in Tribological Sensor Data. DaWaK (2024)
Jonas Hanselle, Stefan Heid, Johannes Fürnkranz, Eyke Hüllermeier
Probabilistic Scoring Lists for Interpretable Machine Learning. CoRR (2024)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Efficiently Training Neural Networks for Imperfect Information Games by Sampling Information Sets. CoRR (2024)
Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier
Probabilistic Scoring Lists for Interpretable Machine Learning. DS (2023)
Florian Beck, Johannes Fürnkranz, Phuong Huynh Van Quoc
Generalizing Conjunctive and Disjunctive Rule Learning to Learning m-of-n Concepts. ITAT (2023)
Phuong Huynh Van Quoc, Johannes Fürnkranz, Florian Beck
Efficient learning of large sets of locally optimal classification rules. Mach. Learn. 112 (2) (2023)
Eneldo Loza Mencía, Moritz Kulessa, Simon Bohlender, Johannes Fürnkranz
Tree-based dynamic classifier chains. Mach. Learn. 112 (11) (2023)
Phuong Huynh Van Quoc, Johannes Fürnkranz, Florian Beck
Efficient learning of large sets of locally optimal classification rules. CoRR (2023)
Anna-Christina Glock, Florian Sobieczky, Johannes Fürnkranz, Peter Filzmoser, Martin Jech
Predictive change point detection for heterogeneous data. CoRR (2023)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Weighting Information Sets with Siamese Neural Networks in Reconnaissance Blind Chess. CoG (2023)
Florian Beck, Johannes Fürnkranz, Phuong Huynh Van Quoc
Layerwise Learning of Mixed Conjunctive and Disjunctive Rule Sets. RuleML+RR (2023)
Johannes Fürnkranz
Towards Deep and Interpretable Rule Learning (invited paper). ITAT (2022)
Antonella Plaia, Simona Buscemi, Johannes Fürnkranz, Eneldo Loza Mencía
Comparing Boosting and Bagging for Decision Trees of Rankings. J. Classif. 39 (1) (2022)
Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencía, Johannes Fürnkranz, Michael Rapp
A flexible class of dependence-aware multi-label loss functions. Mach. Learn. 111 (2) (2022)
Phuong Huynh Van Quoc, Florian Beck, Johannes Fürnkranz
Incremental Update of Locally Optimal Classification Rules. DS (2022)
Aïssatou Diallo, Johannes Fürnkranz
GausSetExpander: A Simple Approach for Entity Set Expansion. CoRR (2022)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess. CoG (2022)
Florian Beck, Johannes Fürnkranz, Phuong Huynh Van Quoc
On the Incremental Construction of Deep Rule Theories. ITAT (2022)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability. CoRR (2022)
Aïssatou Diallo, Johannes Fürnkranz
Unsupervised Alignment of Distributional Word Embeddings. KI (2022)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess. CoRR (2022)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking. CoRR (2021)
Florian Beck, Johannes Fürnkranz
An Empirical Investigation into Deep and Shallow Rule Learning. CoRR (2021)
Florian Beck, Johannes Fürnkranz, Phuong Huynh Van Quoc
Structuring Rule Sets Using Binary Decision Diagrams. RuleML+RR (2021)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier
Gradient-Based Label Binning in Multi-label Classification. ECML/PKDD (3) (2021)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier
Gradient-based Label Binning in Multi-label Classification. CoRR (2021)
Florian Beck, Johannes Fürnkranz
An Empirical Investigation Into Deep and Shallow Rule Learning. Frontiers Artif. Intell. 4 (2021)
Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. Artif. Intell. 295 (2021)
Aïssatou Diallo, Johannes Fürnkranz
Elliptical Ordinal Embedding. CoRR (2021)
Jessica Fritz, Johannes Fürnkranz
Some Chess-Specific Improvements for Perturbation-Based Saliency Maps. CoG (2021)
Timo Bertram, Johannes Fürnkranz, Martin Müller
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking. CoG (2021)
Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Revisiting Non-specific Syndromic Surveillance. IDA (2021)
Tobias Joppen, Johannes Fürnkranz
Ordinal Monte Carlo Tree Search. CoRR (2021)
Eneldo Loza Mencía, Moritz Kulessa, Simon Bohlender, Johannes Fürnkranz
Tree-Based Dynamic Classifier Chains. CoRR (2021)
Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Revisiting Non-Specific Syndromic Surveillance. CoRR (2021)
Aïssatou Diallo, Johannes Fürnkranz
Elliptical Ordinal Embedding. DS (2021)
Aïssatou Diallo, Johannes Fürnkranz
Learning Ordinal Embedding from Sets. Entropy 23 (8) (2021)
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
The Machine Reconnaissance Blind Chess Tournament of NeurIPS 2022. NeurIPS (Competition and Demos) (2021)
Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance. Comput. 10 (3) (2021)
Michael Rapp, Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance. Frontiers Big Data 4 (2021)
Moritz Kulessa, Bennet Wittelsbach, Eneldo Loza Mencía, Johannes Fürnkranz
Sum-Product Networks for Early Outbreak Detection of Emerging Diseases. AIME (2021)
Florian Beck, Johannes Fürnkranz
An Investigation into Mini-Batch Rule Learning. CoRR (2021)
Timo Bertram, Johannes Fürnkranz, Martin Müller
A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems. CoRR (2021)
Michael Rapp, Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Correlation-based Discovery of Disease Patterns for Syndromic Surveillance. CoRR (2021)
Florian Beck, Johannes Fürnkranz
Beyond DNF: First Steps towards Deep Rule Learning. ITAT (2021)
Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía
Conformal Rule-Based Multi-label Classification. KI (2020)
Aïssatou Diallo, Markus Zopf, Johannes Fürnkranz
Permutation Learning via Lehmer Codes. ECAI (2020)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
Learning Gradient Boosted Multi-label Classification Rules. CoRR (2020)
Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim
On cognitive preferences and the plausibility of rule-based models. Mach. Learn. 109 (4) (2020)
Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
On Aggregation in Ensembles of Multilabel Classifiers. CoRR (2020)
Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencía, Johannes Fürnkranz, Michael Rapp
A Flexible Class of Dependence-aware Multi-Label Loss Functions. CoRR (2020)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
Learning Gradient Boosted Multi-label Classification Rules. ECML/PKDD (3) (2020)
Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
On Aggregation in Ensembles of Multilabel Classifiers. DS (2020)
Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, Vu-Linh Nguyen, Michael Rapp
Rule-Based Multi-label Classification: Challenges and Opportunities. RuleML+RR (2020)
Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía, Michael Rapp
Learning Structured Declarative Rule Sets - A Challenge for Deep Discrete Learning. CoRR (2020)
Johannes Czech, Moritz Willig, Alena Beyer, Kristian Kersting, Johannes Fürnkranz
Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data. Frontiers Artif. Intell. 3 (2020)
Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía
Conformal Rule-Based Multi-label Classification. CoRR (2020)
Jinseok Nam, Young-Bum Kim, Eneldo Loza Mencía, Sunghyun Park, Ruhi Sarikaya, Johannes Fürnkranz
Learning Context-dependent Label Permutations for Multi-label Classification. ICML (2019)
Tobias Joppen, Tilman Strübig, Johannes Fürnkranz
Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation. CoRR (2019)
Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
Advances in Machine Learning for the Behavioral Sciences. CoRR (2019)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy. CoRR (2019)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics. CoRR (2019)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics. DS (2019)
Sebastian Kauschke, Lukas Fleckenstein, Johannes Fürnkranz
Mending is Better than Ending: Adapting Immutable Classifiers to Nonstationary Environments using Ensembles of Patches. IJCNN (2019)
Hien Q. Dang, Johannes Fürnkranz
Driver Information Embedding with Siamese LSTM networks. IV (2019)
Johannes Czech, Moritz Willig, Alena Beyer, Kristian Kersting, Johannes Fürnkranz
Learning to play the Chess Variant Crazyhouse above World Champion Level with Deep Neural Networks and Human Data. CoRR (2019)
Tobias Joppen, Johannes Fürnkranz
Ordinal Monte Carlo Tree Search. CoRR (2019)
Tobias Joppen, Tilman Strübig, Johannes Fürnkranz
Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation. CoG (2019)
Aïssatou Diallo, Markus Zopf, Johannes Fürnkranz
Improving Answer Selection with Analogy-Preserving Sentence Embeddings. LWDA (2019)
Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Improving the Fusion of Outbreak Detection Methods with Supervised Learning. CIBB (2019)
Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
Improving Outbreak Detection with Stacking of Statistical Surveillance Methods. CoRR (2019)
Alexander Zap, Tobias Joppen, Johannes Fürnkranz
Deep Ordinal Reinforcement Learning. ECML/PKDD (3) (2019)
Lukas Fleckenstein, Sebastian Kauschke, Johannes Fürnkranz
Beta Distribution Drift Detection for Adaptive Classifiers. ESANN (2019)
Aïssatou Diallo, Markus Zopf, Johannes Fürnkranz
Learning Analogy-Preserving Sentence Embeddings for Answer Selection. CoNLL (2019)
Julian Schwehr, Stefan Luthardt, Hien Q. Dang, Maren Henzel, Hermann Winner, Jürgen Adamy, Johannes Fürnkranz, Volker Willert, Benedikt Lattke, Maximilian Höpfl, Christoph Wannemacher
The PRORETA 4 City Assistant System. Autom. 67 (9) (2019)
Sebastian Kauschke, David Hermann Lehmann, Johannes Fürnkranz
Patching Deep Neural Networks for Nonstationary Environments. IJCNN (2019)
Alexander Zap, Tobias Joppen, Johannes Fürnkranz
Deep Ordinal Reinforcement Learning. CoRR (2019)
Aïssatou Diallo, Markus Zopf, Johannes Fürnkranz
Learning Analogy-Preserving Sentence Embeddings for Answer Selection. CoRR (2019)
Maryam Tavakol, Tobias Joppen, Ulf Brefeld, Johannes Fürnkranz
Personalized Transaction Kernels for Recommendation Using MCTS. KI (2019)
Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim
On Cognitive Preferences and the Interpretability of Rule-based Models. CoRR (2018)
Sebastian Kauschke, Max Mühlhäuser, Johannes Fürnkranz
Leveraging Reproduction-Error Representations for Multi-Instance Classification. DS (2018)
Lukas Fleckenstein, Sebastian Kauschke, Johannes Fürnkranz
Beta Distribution Drift Detection for Adaptive Classifiers. CoRR (2018)
Johannes Fürnkranz, Tomás Kliegr
The Need for Interpretability Biases. IDA (2018)
Tobias Joppen, Christian Wirth, Johannes Fürnkranz
Preference-Based Monte Carlo Tree Search. CoRR (2018)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules. CoRR (2018)
Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. CoRR (2018)
Sebastian Kauschke, Max Mühlhäuser, Johannes Fürnkranz
Towards Semi-Supervised Classification of Event Streams via Denoising Autoencoders. ICMLA (2018)
Tobias Joppen, Miriam Ulrike Moneke, Nils Schröder, Christian Wirth, Johannes Fürnkranz
Informed Hybrid Game Tree Search for General Video Game Playing. IEEE Trans. Games 10 (1) (2018)
Hien Q. Dang, Johannes Fürnkranz
Exploiting Maneuver Dependency for Personalization of a Driver Model. LWDA (2018)
Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier, Michael Rapp
Learning Interpretable Rules for Multi-label Classification. CoRR (2018)
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules. PAKDD (1) (2018)
Sebastian Kauschke, Johannes Fürnkranz
Batchwise Patching of Classifiers. AAAI (2018)
Markus Zopf, Teresa Botschen, Tobias Falke, Benjamin Heinzerling, Ana Marasovic, Todor Mihaylov, Avinesh P. V. S., Eneldo Loza Mencía, Johannes Fürnkranz, Anette Frank
What's Important in a Text? An Extensive Evaluation of Linguistic Annotations for Summarization. SNAMS (2018)
Markus Zopf, Eneldo Loza Mencía, Johannes Fürnkranz
Which Scores to Predict in Sentence Regression for Text Summarization? NAACL-HLT (2018)
Hien Q. Dang, Johannes Fürnkranz
Using Past Maneuver Executions for Personalization of a Driver Model. ITSC (2018)
Tobias Joppen, Christian Wirth, Johannes Fürnkranz
Preference-Based Monte Carlo Tree Search. KI (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Johannes Fürnkranz