Johannes Fürnkranz

Johannes Fürnkranz, Eneldo Loza Mencía, Johannes Fürnkranz, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

On Cognitive Preferences and the Interpretability of Rule-based Models pdf

Johannes Fürnkranz, Heiko Paulheim, Tomás Kliegr, 2018, ArXiv.

Report on the Machine-Learning in Game-Playing Workshop

Johannes Fürnkranz, Moroslaw Kubat, 1999, J. Int. Comput. Games Assoc..

Pruning Algorithms for Rule Learning

Johannes Fürnkranz, Johannes Fürnkranz, 1997, Machine Learning.

On exploiting hierarchical label structure with pairwise classifiers

Johannes Fürnkranz, Jan Frederik Sima, 2011, SKDD.

On Meta-Learning Rule Learning Heuristics

Johannes Fürnkranz, Frederik Janssen, Johannes Fürnkranz, 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

Web Mining

Johannes Fürnkranz, Johannes Fürnkranz, 2005, Data Mining and Knowledge Discovery Handbook.

Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning

Johannes Fürnkranz, Eneldo Loza Mencía, Hyunwoo J. Kim, 2015, ECML/PKDD.

Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns

Johannes Fürnkranz, Wouter Duivesteijn, Arno J. Knobbe, 2012, IDA.

Rule-Based Multi-label Classification: Challenges and Opportunities

Johannes Fürnkranz, Eneldo Loza Mencía, Eyke Hüllermeier, 2020, RuleML+RR.

A Study Using $n$-gram Features for Text Categorization

Johannes Fürnkranz, Johannes Fürnkranz, 1998 .

Towards Semi-Supervised Classification of Event Streams via Denoising Autoencoders

Johannes Fürnkranz, Max Mühlhäuser, Sebastian Kauschke, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain

Johannes Fürnkranz, Eneldo Loza Mencía, 2007, LWA.

First Steps Towards Learning from Game Annotations

Johannes Fürnkranz, Christian Wirth, Johannes Fürnkranz, 2012 .

Machine learning in games: a survey

Johannes Fürnkranz, Johannes Fürnkranz, 2001 .

Preference Learning

Eyke Hüllermeier, Johannes Fürnkranz, Johannes Fürnkranz, 2005, Künstliche Intell..

Beyond Concept Learning

Johannes Fürnkranz, Dragan Gamberger, Nada Lavrač, 2012 .

Driver Information Embedding with Siamese LSTM networks

Johannes Fürnkranz, Hien Dang, 2019, 2019 IEEE Intelligent Vehicles Symposium (IV).

A review and comparison of strategies for handling missing values in separate-and-conquer rule learning

Johannes Fürnkranz, Lars Wohlrab, Johannes Fürnkranz, 2011, Journal of Intelligent Information Systems.

An Analysis of Stopping and Filtering Criteria for Rule Learning

Johannes Fürnkranz, Peter A. Flach, 2004, ECML.

An Exploitative Monte-Carlo Poker Agent

Johannes Fürnkranz, Sang-Hyeun Park, Kamill Panitzek, 2009, LWA.

Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules

Johannes Fürnkranz, Eneldo Loza Mencía, Michael Rapp, 2018, PAKDD.

Learning Context-dependent Label Permutations for Multi-label Classification

Johannes Fürnkranz, Ruhi Sarikaya, Eneldo Loza Mencía, 2019, ICML.

On Minimizing the Position Error in Label Ranking

Eyke Hüllermeier, Johannes Fürnkranz, 2007, ECML.

Process-Based Modeling

Stan Matwin, Eyke Hüllermeier, Johannes Fürnkranz, 2010, Encyclopedia of Machine Learning.

Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization

Johannes Fürnkranz, Eneldo Loza Mencía, Markus Zopf, 2016, CoNLL.

Preference Learning and Ranking by Pairwise Comparison

Eyke Hüllermeier, Johannes Fürnkranz, Johannes Fürnkranz, 2010, Preference Learning.

A Comparison of Techniques for Selecting and Combining Class Association Rules

Johannes Fürnkranz, Jan-Nikolas Sulzmann, Johannes Fürnkranz, 2008, LWA.

Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach

Johannes Fürnkranz, Francesco C. Billari, Alexia Prskawetz, 2000 .

ROC Curve

Risto Miikkulainen, Johannes Fürnkranz, Jun Morimoto, 2010, Encyclopedia of Machine Learning.

The Role of Qualitative Knowledge in Machine Learning

Johannes Fürnkranz, Johannes Fürnkranz, 1993 .

Multi-objective Optimisation-Based Feature Selection for Multi-label Classification

Johannes Fürnkranz, Asif Ekbal, Eneldo Loza Mencía, 2017, NLDB.

Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization

Johannes Fürnkranz, Eneldo Loza Mencía, Markus Zopf, 2016, COLING.

From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms

Johannes Fürnkranz, Johannes Fürnkranz, 2004, Local Pattern Detection.

Market Basket Analysis

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification

Johannes Fürnkranz, Eneldo Loza Mencía, Hyunwoo J. Kim, 2017, NIPS.

Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy pdf

Johannes Fürnkranz, Michael Rapp, Eneldo Loza Mencía, 2019, ArXiv.

Eine Grafische Benutzeroberfläche für ein Poker-Spiel

Johannes Fürnkranz, Fachbereich Informatik, 2011 .

A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning

Johannes Fürnkranz, Frederik Janssen, 2008, LWA.

Machine learning and games

Johannes Fürnkranz, Michael H. Bowling, Thore Graepel, 2006, Machine Learning.

Proceedings of the ECML/PKDD-13 Workshop on Reinforcement Learning with Generalized Feedback: Beyond Numeric Rewards

Eyke Hüllermeier, Johannes Fürnkranz, 2013 .

An Analysis of Rule Evaluation Metrics

Johannes Fürnkranz, Peter A. Flach, Johannes Fürnkranz, 2003, ICML.

Comparison of Ranking Procedures in Pairwise Preference Learning

Eyke Hüllermeier, Johannes Fürnkranz, Johannes Fürnkranz, 2004 .

Formal Framework for Rule Analysis

Johannes Fürnkranz, Dragan Gamberger, Nada Lavrač, 2012 .

Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms

Johannes Fürnkranz, Nada Lavrac, Dragan Gamberger, 2010, Advances in Machine Learning I.

Adaptive Support of Knowledge Work by Analysis of User Objectives

Johannes Fürnkranz, Matthaus Martynus, 2008 .

Machine Learning Methods for International Conflict Databases: A Case Study in Predicting Mediation Outcome

Johannes Fürnkranz, Robert Trappl, Johann Petrak, 1994 .

Efficient implementation of class-based decomposition schemes for Naïve Bayes

Johannes Fürnkranz, Sang-Hyeun Park, 2013, Machine Learning.

Exploiting Maneuver Dependency for Personalization of a Driver Model

Johannes Fürnkranz, Hien Q. Dang, 2018, LWDA.

Random Decision Forests

Risto Miikkulainen, Johannes Fürnkranz, Jun Morimoto, 2010, Encyclopedia of Machine Learning.

Report on ALIS Ontology

Johannes Fürnkranz, Giuseppe Contissa, Migle Laukyte, 2008 .

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

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006, PKDD.

Rule Learning in a Nutshell

Johannes Fürnkranz, Dragan Gamberger, Nada Lavrač, 2012 .

Informed Hybrid Game Tree Search for General Video Game Playing

Johannes Fürnkranz, Christian Wirth, Tobias Joppen, 2017, IEEE Transactions on Games.

Decision List

Johannes Fürnkranz, 2010, Encyclopedia of Machine Learning.

Learning Label Preferences: Ranking Error Versus Position Error

Eyke Hüllermeier, Johannes Fürnkranz, 2005, IDA.

Special Issue on Machine Learning and Games

Johannes Fürnkranz, Michael H. Bowling, Michael Bowling, 2006 .

Rule Learning

Johannes Fürnkranz, Johannes Fürnkranz, 2010, Encyclopedia of Machine Learning and Data Mining.

Knowledge Discovery in Databases: PKDD 2006: 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September ... (Lecture Notes in Computer Science)

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006 .

Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006, ECML.

Proceedings of the ECAI-12 Workshop on Preference Learning: Problems and Applications in AI (PL-12)

Eyke Hüllermeier, Johannes Fürnkranz, Johannes Fürnkranz, 2012 .

Special Issue on First-Order Knowledge Discovery in Databases

Johannes Fürnkranz, Bernhard Pfahringer, 1998 .

Learning to Make Good Use of Operational Advice

Johannes Fürnkranz, Stefan Kramer, Bernhard Pfahringer, 1999 .

Conformal Rule-Based Multi-label Classification

Johannes Fürnkranz, Eneldo Loza Mencía, Eyke Hüllermeier, 2020, KI.

A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning

Johannes Fürnkranz, 2002, ALT.

Special Issue on Discovery Science

Eyke Hüllermeier, Johannes Fürnkranz, 2016, Inf. Sci..

A Hypothesis on the Divergence of AI Research

Johannes Fürnkranz, Franz-Günter Winkler, Johannes Fürnkranz, 1998, J. Int. Comput. Games Assoc..

Editorial: Preference learning and ranking

Eyke Hüllermeier, Johannes Fürnkranz, 2013, Machine Learning.

Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach

Johannes Fürnkranz, Nada Lavrac, Dragan Gamberger, 2008, PRICAI.

Label ranking by learning pairwise preferences

Eyke Hüllermeier, Johannes Fürnkranz, Klaus Brinker, 2008, Artif. Intell..

Combining Pairwise Classifiers with Stacking

Johannes Fürnkranz, Petr Savický, 2003, IDA.

Machines that learn to play games

Johannes Fürnkranz, Miroslav Kubat, 2001 .

Guest Editorial: Machine Learning and Games

Johannes Fürnkranz, Michael H. Bowling, Michael Bowling, 2006 .

Round robin ensembles

Johannes Fürnkranz, Johannes Fürnkranz, 2003, Intell. Data Anal..

Learning Rule Sets

Johannes Fürnkranz, Dragan Gamberger, Nada Lavrač, 2012 .

Machines That Learn to Play Games: Volume 8 in the Advances in Computation: Theory and Practice

Johannes Fürnkranz, Miroslav Kubat, Johannes Fürnkranz, 2001 .

Receiver Operating Characteristic Analysis

Risto Miikkulainen, Johannes Fürnkranz, Luís Torgo, 2010, Encyclopedia of Machine Learning.

Covering Algorithm

Johannes Fürnkranz, Johannes Fürnkranz, 2017, Encyclopedia of Machine Learning and Data Mining.

The Potential Contribution of AI to the Avoidance of Crises and Wars: Using CBR Methods with the KOSIMO Database of Conflicts

Johannes Fürnkranz, Robert Trappl, Johann Petrak, 1994 .

A review of possible effects of cognitive biases on interpretation of rule-based machine learning models pdf

Johannes Fürnkranz, Stepán Bahník, Tomás Kliegr, 2018, Artif. Intell..

Personalized Transaction Kernels for Recommendation Using MCTS

Johannes Fürnkranz, Ulf Brefeld, Tobias Joppen, 2019, KI.

Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning

Johannes Fürnkranz, Julius Stecher, Frederik Janssen, 2014, ECML/PKDD.

Preference Learning (Dagstuhl Seminar 14101)

Eyke Hüllermeier, Johannes Fürnkranz, Scott Sanner, 2014, Dagstuhl Reports.

Mean Squared Error

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Event-Based Clustering for Reducing Labeling Costs of Event-related Microposts

Johannes Fürnkranz, Axel Schulz, Frederik Janssen, 2015, ICWSM.

Application of Machine Learning Methods to the KOSIMO Database

Johannes Fürnkranz, Johannes Fürnkranz, 1993 .

A Comparison of Pruning Methods for Relational Concept Learning

Johannes Fürnkranz, Johannes Fürnkranz, 1994, KDD Workshop.

Graded Multilabel Classification by Pairwise Comparisons

Johannes Fürnkranz, Eneldo Loza Mencía, Christian Brinker, 2014, 2014 IEEE International Conference on Data Mining.

Supervised Descriptive Rule Learning

Johannes Fürnkranz, Dragan Gamberger, Nada Lavrač, 2012 .

Decision Tree

Johannes Fürnkranz, 2017, Encyclopedia of Machine Learning and Data Mining.

A Unified Model for Multilabel Classification and Ranking

Eyke Hüllermeier, Johannes Fürnkranz, Klaus Brinker, 2006, ECAI.

Bericht über {The 13th International Conference on Artificial Intelligence (IJCAI-93)}

Johannes Fürnkranz, 1993 .

Large-Scale Multi-label Text Classification - Revisiting Neural Networks

Johannes Fürnkranz, Iryna Gurevych, Jungi Kim, 2013, ECML/PKDD.

ROC ‘n’ Rule Learning—Towards a Better Understanding of Covering Algorithms

Johannes Fürnkranz, Peter A. Flach, Johannes Fürnkranz, 2005, Machine Learning.

A Brief Introduction to Knowledge Discovery in Databases

Johannes Fürnkranz, 1995 .

Advances in Machine Learning for the Behavioral Sciences

Johannes Fürnkranz, Stepán Bahník, Tomás Kliegr, 2019, American Behavioral Scientist.

Learning to Use Operational Advice

Johannes Fürnkranz, Hermann Kaindl, Stefan Kramer, 2000, ECAI.

Machine Learning and Data Mining

Johannes Fürnkranz, Dragan Gamberger, Nada Lavrač, 2012 .

Using semantic similarity for multi-label zero-shot classification of text documents

Johannes Fürnkranz, Eneldo Loza Mencía, Jinseok Nam, 2016, ESANN.

Machine Learning in Computer Chess: The Next Generation

Johannes Fürnkranz, Johannes Fürnkranz, 1996, J. Int. Comput. Games Assoc..

Proceedings of the 17th European conference on Machine Learning

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006 .

Advances in Efficient Pairwise Multilabel Classification

Johannes Fürnkranz, Eneldo Loza Mencía, Sang-Hyeun Park, 2008 .

On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics pdf

Johannes Fürnkranz, Eneldo Loza Mencía, Michael Rapp, 2019, DS.

Proceedings of the 16th International Conference on Discovery Science (DS-13)

Eyke Hüllermeier, Johannes Fürnkranz, Tomoyuki Higuchi, 2013 .

Rank Correlation

Eyke Hüllermeier, Johannes Fürnkranz, Russ Tedrake, 2010, Encyclopedia of Machine Learning and Data Mining.

Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel

Johannes Fürnkranz, Thorsten Joachims, T. Joachims, 2010, ICML.

Efficient Pairwise Classification

Johannes Fürnkranz, Sang-Hyeun Park, Johannes Fürnkranz, 2007, ECML.

Rule Evaluation Measures

Johannes Fürnkranz, Nada Lavrač, Dragan Gamberger, 2012 .

KI 2017: Advances in Artificial Intelligence

Johannes Fürnkranz, Gabriele Kern-Isberner, Matthias Thimm, 2017, Lecture Notes in Computer Science.

Multistrategy Ensemble Learning

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Top-Down Pruning in Relational Learning

Johannes Fürnkranz, 1994, ECAI.

Class Binarization

Johannes Fürnkranz, Johannes Fürnkranz, 2017, Encyclopedia of Machine Learning and Data Mining.

Lernen Abalone zu Spielen Bachelorarbeit

Johannes Fürnkranz, Fachbereich Informatik, Fachgebiet Knowledge Engeneering, 2010 .

On Trading Off Consistency and Coverage in Inductive Rule Learning

Johannes Fürnkranz, Frederik Janssen, 2006, LWA.

Proceedings of the ICML-99 Workshop on Machine Learning in Game Playing

Johannes Fürnkranz, Miroslav Kubat, Johannes Fürnkranz, 1999 .

User profiling for the melvil knowledge retrieval system

Johannes Fürnkranz, Christian Holzbaur, Robert Temel, 2002, Appl. Artif. Intell..

Probability Estimation and Aggregation for Rule Learning

Johannes Fürnkranz, Jan-Nikolas Sulzmann, 2010, LWA.

Rule-Based Methods

Johannes Fürnkranz, Johannes Fürnkranz, 2013 .

Dimensionality Reduction in ILP: A Call to Arms

Johannes Fürnkranz, Johannes Fürnkranz, 1997 .

Unsupervised generation of data mining features from linked open data

Johannes Fürnkranz, Heiko Paulheim, Johannes Fürnkranz, 2012, WIMS '12.

Using Past Maneuver Executions for Personalization of a Driver Model

Johannes Fürnkranz, Hien Q. Dang, 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

Integrative Windowing

Johannes Fürnkranz, Johannes Fürnkranz, 1998, J. Artif. Intell. Res..

Predictive software models

Stan Matwin, Eyke Hüllermeier, Johannes Fürnkranz, 2004, Conference on Semantics in Text Processing.

An Evaluation of Grading Classifiers

Johannes Fürnkranz, Alexander K. Seewald, Johannes Fürnkranz, 2001, IDA.

A Policy Iteration Algorithm for Learning from Preference-Based Feedback

Johannes Fürnkranz, Christian Wirth, Johannes Fürnkranz, 2013, IDA.

Using Links for Classifying Web-Pages

Johannes Fürnkranz, Johannes Fürnkranz, 1998 .

Pruning of Rules and Rule Sets

Johannes Fürnkranz, Dragan Gamberger, Nada Lavrač, 2012 .

Multi-Armed Bandit

Johannes Fürnkranz, Luís Torgo, Katharina Morik, 2010, Encyclopedia of Machine Learning.

Missing Values

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Separate-and-conquer Regression

Johannes Fürnkranz, Frederik Janssen, Johannes Fürnkranz, 2010, LWA.

EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning

Johannes Fürnkranz, Christian Wirth, Johannes Fürnkranz, 2013, ACML.

Improving the Fusion of Outbreak Detection Methods with Supervised Learning

Johannes Fürnkranz, Eneldo Loza Mencía, Moritz Kulessa, 2019, CIBB.

More Efficient Windowing

Johannes Fürnkranz, Johannes Fürnkranz, 1997, AAAI/IAAI.

Dual Control

Johannes Fürnkranz, Marko Grobelnik, George Karypis, 2010, Encyclopedia of Machine Learning.

Decision Stump

Johannes Fürnkranz, Marko Grobelnik, George Karypis, 2010, Encyclopedia of Machine Learning.

Preference Learning: An Introduction

Eyke Hüllermeier, Johannes Fürnkranz, Johannes Fürnkranz, 2010, Preference Learning.

Ranking by pairwise comparison a note on risk minimization

Eyke Hüllermeier, Johannes Fürnkranz, Johannes Fürnkranz, 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

Erratum to: Predicting unseen labels using label hierarchies in large-scale multi-label learning

Johannes Fürnkranz, Eneldo Loza Mencía, Hyunwoo Kim, 2015 .

Preference Learning from Annotated Game Databases

Johannes Fürnkranz, Christian Wirth, Johannes Fürnkranz, 2014, LWA.

PLAY: A Profiled Linear Weighting Scheme for Understanding the Influence of Input Variables on the Output of a Deep Artificial Neural Network

Johannes Fürnkranz, Gjergji Kasneci, Eneldo Loza Mencía, 2020 .

Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning

Eyke Hüllermeier, Johannes Fürnkranz, Sang-Hyeun Park, 2011, ECML/PKDD.

From Local Patterns to Global Models: Proceedings of the ECML/PKDD-08 Workshop

Johannes Fürnkranz, Arno Knobbe, Johannes Fürnkranz, 2008 .

Learning Interpretable Rules for Multi-label Classification pdf

Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, 2018, ArXiv.

Predicting Cargo Train Failures: A Machine Learning Approach for a Lightweight Prototype

Johannes Fürnkranz, Frederik Janssen, Sebastian Kauschke, 2016, DS.

Heuristic Rule-Based Regression via Dynamic Reduction to Classification

Johannes Fürnkranz, Frederik Janssen, Johannes Fürnkranz, 2011, IJCAI.

Guest Editorial: First-Order Knowledge Discovery in Databases

Johannes Fürnkranz, Bernhard Pfahringer, 1998, Appl. Artif. Intell..

Link-Local Features for Hypertext Classification

Johannes Fürnkranz, Hervé Utard, Johannes Fürnkranz, 2005, EWMF/KDO.

Permutation Learning via Lehmer Codes

Johannes Fürnkranz, Markus Zopf, Aïssatou Diallo, 2020, ECAI.

Web Structure Mining --- Exploiting the Graph Structure of the World-Wide Web

Johannes Fürnkranz, Johannes Fürnkranz, 2002 .

From Local Patterns to Global Models: The LeGo Approach to Data Mining

Johannes Fürnkranz, Bruno Crémilleux, Martin Scholz, 2008 .

Learning Playing Strategies from Chess Endgame Databases: An ILP Approach

Luc De Raedt, Johannes Fürnkranz, L. D. Raedt, 1997 .

LEARNING TO RECOGNIZE MISSING E-MAIL ATTACHMENTS

Johannes Fürnkranz, Marco Ghiglieri, 2010, Appl. Artif. Intell..

Workshop Report: Machine Learning in Game Playing

Johannes Fürnkranz, Miroslav Kubat, Johannes Fürnkranz, 1999 .

Learning Gradient Boosted Multi-label Classification Rules pdf

Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, 2020, ArXiv.

Ordinal Monte Carlo Tree Search pdf

Johannes Fürnkranz, Tobias Joppen, 2019, ArXiv.

Exploiting Code Redundancies in ECOC

Johannes Fürnkranz, Lorenz Weizsäcker, Sang-Hyeun Park, 2010, Discovery Science.

Multi-Label Classification with Label Constraints

Johannes Fürnkranz, Sang-Hyeun Park, 2008 .

A Survey of Preference-Based Reinforcement Learning Methods

Johannes Fürnkranz, Christian Wirth, Gerhard Neumann, 2017, J. Mach. Learn. Res..

A Comparison of Strategies for Handling Missing Values in Rule Learning

Johannes Fürnkranz, Lars Wohlrab, 2009 .

Rule Learning

Johannes Fürnkranz, Johannes Fürnkranz, 2010, Encyclopedia of Machine Learning and Data Mining.

Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction

Johannes Fürnkranz, Sang-Hyeun Park, Johannes Fürnkranz, 2012, Discovery Science.

Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression

Johannes Fürnkranz, Andrei Tolstikov, Frederik Janssen, 2017, DS.

Preference-Based Monte Carlo Tree Search pdf

Johannes Fürnkranz, Christian Wirth, Tobias Joppen, 2018, KI.

Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data

Johannes Fürnkranz, Kristian Kersting, Johannes Czech, 2020, Frontiers in Artificial Intelligence.

Basic Instrument for Experimental Probes in Machine Learning

Johannes Fürnkranz, Lorenz Weizsäcker, 2012 .

The Need for Interpretability Biases

Johannes Fürnkranz, Tomás Kliegr, 2018, IDA.

Discovery science : 16th international conference, DS 2013, Singapore, October 6-9, 2013 : proceedings

Eyke Hüllermeier, Johannes Fürnkranz, Tomoyuki Higuchi, 2013 .

Learning Structured Declarative Rule Sets - A Challenge for Deep Discrete Learning pdf

Johannes Fürnkranz, Eneldo Loza Mencía, Eyke Hüllermeier, 2020, ArXiv.

The PRORETA 4 City Assistant System

Johannes Fürnkranz, Hermann Winner, Volker Willert, 2019, Autom..

Knowledge Discovery in Chess Databases: A Research Proposal

Johannes Fürnkranz, Johannes Fürnkranz, 1997 .

On cognitive preferences and the plausibility of rule-based models

Johannes Fürnkranz, Heiko Paulheim, Tomáš Kliegr, 2018, Machine Learning.

Recent Advances in Machine Learning and Game Playing

Johannes Fürnkranz, Johannes Fürnkranz, 2007 .

Foundations of Rule Learning

Johannes Fürnkranz, Nada Lavrac, Dragan Gamberger, 2012, Cognitive Technologies.

On Effort in AI Research: A Description Along Two Dimensions

Johannes Fürnkranz, Franz-Günter Winkler, Johannes Fürnkranz, 1997, Deep Blue Versus Kasparov: The Significance for Artificial Intelligence.

On the quest for optimal rule learning heuristics

Johannes Fürnkranz, Frederik Janssen, Johannes Fürnkranz, 2010, Machine Learning.

Proceedings of the ECML/PKDD-04 Workshop on Advances in Inductive Rule Learning

Johannes Fürnkranz, 2004 .

Exploiting Code-Redundancies in ECOC for Reducing its Training Complexity using Incremental and

Johannes Fürnkranz, Lorenz Weizsäcker, Sang-Hyeun Park, 2010 .

The Potential Contribution of AI to the Avoidance of Crises and Wars: Bibliography

Johannes Fürnkranz, Robert Trappl, Johann Petrak, 1994 .

On Pairwise Naive Bayes Classifiers

Eyke Hüllermeier, Johannes Fürnkranz, Jan-Nikolas Sulzmann, 2007, ECML.

Radial Basis Function Neural Networks

Risto Miikkulainen, Johannes Fürnkranz, Jun Morimoto, 2010, Encyclopedia of Machine Learning.

Learning from Label Preferences

Eyke Hüllermeier, Johannes Fürnkranz, 2011, Discovery Science.

Avoiding Noise Fitting in a sc Foil-like Learning Algorithm

Johannes Fürnkranz, Johannes Fürnkranz, 1993 .

Knowledge Discovery in Scientific Literature

Johannes Fürnkranz, Iryna Gurevych, Susanne Neumann, 2014, KONVENS.

Incremental Reduced Error Pruning

Johannes Fürnkranz, Gerhard Widmer, Johannes Fürnkranz, 1994, ICML.

Decision List

Johannes Fürnkranz, 2017, Encyclopedia of Machine Learning and Data Mining.

Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification

Johannes Fürnkranz, Sang-Hyeun Park, Johannes Fürnkranz, 2009, ECML/PKDD.

Divide-and-Conquer Learning

Johannes Fürnkranz, 2017, Encyclopedia of Machine Learning and Data Mining.

Bericht über {The 11th International Conference on Machine Learning (ML-94)}

Johannes Fürnkranz, 1994 .

Which Scores to Predict in Sentence Regression for Text Summarization?

Johannes Fürnkranz, Eneldo Loza Mencía, Markus Zopf, 2018, NAACL-HLT.

Detecting Temporal Change in Event Sequences: An Application to Demographic Data

Johannes Fürnkranz, Hendrik Blockeel, Francesco C. Billari, 2001, PKDD.

On Aggregation in Ensembles of Multilabel Classifiers

Johannes Fürnkranz, Eneldo Loza Mencía, Eyke Hüllermeier, 2020, DS.

Patching Deep Neural Networks for Nonstationary Environments

Johannes Fürnkranz, Sebastian Kauschke, David H. Lehmann, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Round Robin Rule Learning

Johannes Fürnkranz, Johannes Fürnkranz, 2001, ICML.

Noise-Tolerant Windowing

Johannes Fürnkranz, Johannes Fürnkranz, 1997, IJCAI.

A Brief Overview of Rule Learning

Johannes Fürnkranz, Tomás Kliegr, Johannes Fürnkranz, 2015, RuleML.

Principles of Data Mining and Knowledge Discovery

Johannes Fürnkranz, Wei-Min Shen, Hendrik Blockeel, 1997, Lecture Notes in Computer Science.

Efficient Pruning Methods for Relational Learning (Extended Thesis Abstract)

Johannes Fürnkranz, 1995 .

What's Important in a Text? An Extensive Evaluation of Linguistic Annotations for Summarization

Johannes Fürnkranz, Benjamin Heinzerling, Eneldo Loza Mencía, 2018, 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS).

Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain

Johannes Fürnkranz, Eneldo Loza Mencía, Johannes Fürnkranz, 2008, ECML/PKDD.

FOSSIL: A Robust Relational Learner

Johannes Fürnkranz, Johannes Fürnkranz, 1994, ECML.

Round Robin Classification

Johannes Fürnkranz, Johannes Fürnkranz, 2002, J. Mach. Learn. Res..

Time-to-lane-change prediction with deep learning

Johannes Fürnkranz, Alexander Biedermann, Maximilian Höpfl, 2017, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC).

Beta Distribution Drift Detection for Adaptive Classifiers pdf

Johannes Fürnkranz, Sebastian Kauschke, Lukas Fleckenstein, 2018, ESANN.

Divide-and-Conquer Learning

Johannes Fürnkranz, Johannes Fürnkranz, 2010, Encyclopedia of Machine Learning.

Proceedings, Twenty-Seventh International Conference on Machine Learning

Johannes Fürnkranz, Thorsten Joachims, T. Joachims, 2010 .

On the Use of Fast Subsampling Estimates for Algorithm Recommendation

Johannes Fürnkranz, Carlos Soares, Pavel Brazdil, 2002 .

Modeling Rule Precision

Johannes Fürnkranz, 2004, LWA.

Knowledge Discovery in International Conflict Databases

Johannes Fürnkranz, Robert Trappl, Johann Petrak, 1997, Appl. Artif. Intell..

On the Importance of a Hierarchy for Learning Continuous Vector Representations of a Label Space pdf

Johannes Fürnkranz, Jinseok Nam, 2015, ICLR.

Decision Lists and Decision Trees

Johannes Fürnkranz, 2010, Encyclopedia of Machine Learning.

Deep Ordinal Reinforcement Learning

Johannes Fürnkranz, Tobias Joppen, Alexander Zap, 2019, ECML/PKDD.

Learning of Piece Values for Chess Variants

Johannes Fürnkranz, Sacha Droste, Johannes Fürnkranz, 2008 .

A Tight Integration of Pruning and Learning

Johannes Fürnkranz, 1995 .

Learning from Label Preferences

Eyke Hüllermeier, Johannes Fürnkranz, 2011, ALT.

Machine Learning and Game Playing

Johannes Fürnkranz, Johannes Fürnkranz, 2010, Encyclopedia of Machine Learning and Data Mining.

Rule Set

Johannes Fürnkranz, 2017, Encyclopedia of Machine Learning and Data Mining.

Inductive Rule Learning for Data and Web Mining

Johannes Fürnkranz, Johannes Fürnkranz, 2001 .

Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006 .

Interactive Data Analytics for the Humanities

Johannes Fürnkranz, Carsten Binnig, Kristian Kersting, 2017, CICLing.

Mean Absolute Error

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning and Data Mining.

Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases

Johannes Fürnkranz, Robert Trappl, Johann Petrak, 1996, ECAI.

On predictive accuracy and risk minimization in pairwise label ranking

Eyke Hüllermeier, Johannes Fürnkranz, Johannes Fürnkranz, 2010, J. Comput. Syst. Sci..

A Tight Integration of Pruning and Learning (Extended Abstract)

Johannes Fürnkranz, 1995, ECML.

Rule Stacking: An Approach for Compressing an Ensemble of Rule Sets into a Single Classifier

Johannes Fürnkranz, Jan-Nikolas Sulzmann, Johannes Fürnkranz, 2011, Discovery Science.

Decision Lists and Decision Trees

Johannes Fürnkranz, 2010 .

An Empirical Comparison of Techniques for Selecting and Combining Local Patterns into a Global Model

Johannes Fürnkranz, Jan-Nikolas Sulzmann, Johannes Fürnkranz, 2008 .

Preference-Based Reinforcement Learning: A Preliminary Survey

Johannes Fürnkranz, Christian Wirth, Johannes Fürnkranz, 2013 .

Decision Tree

Johannes Fürnkranz, Johannes Fürnkranz, 2010, Encyclopedia of Machine Learning and Data Mining.

Meta-Learning a Rule Learning Heuristic

Johannes Fürnkranz, Frederik Janssen, Johannes Fürnkranz, 2007 .

Model-Free Preference-Based Reinforcement Learning

Johannes Fürnkranz, Christian Wirth, Gerhard Neumann, 2016, AAAI.

The SeCo-framework for rule learning

Johannes Fürnkranz, Frederik Janssen, 2010 .

Learning the Piece Values for Three Chess Variants

Johannes Fürnkranz, Sacha Droste, Johannes Fürnkranz, 2008, J. Int. Comput. Games Assoc..

News

Johannes Fürnkranz, 2017, KI - Künstliche Intelligenz.

Mending is Better than Ending: Adapting Immutable Classifiers to Nonstationary Environments using Ensembles of Patches

Johannes Fürnkranz, Sebastian Kauschke, Lukas Fleckenstein, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

MACHINE LEARNING AND CASE-BASED REASONING: THEIR POTENTIAL ROLE IN PREVENTING THE OUTBREAK OF WARS OR IN ENDING THEM

Johannes Fürnkranz, Robert Trappl, Johann Petrak, 1997 .

An Evaluation of Landmarking Variants

Johannes Fürnkranz, Johann Petrak, Johannes Fürnkranz, 2001 .

What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation

Johannes Fürnkranz, Jinseok Nam, Fabian Hirschmann, 2016, COLING.

Batchwise Patching of Classifiers

Johannes Fürnkranz, Sebastian Kauschke, Johannes Fürnkranz, 2018, AAAI.

Decision Stump

Johannes Fürnkranz, Johannes Fürnkranz, 2017, Encyclopedia of Machine Learning and Data Mining.

Preference-based reinforcement learning: a formal framework and a policy iteration algorithm

Eyke Hüllermeier, Johannes Fürnkranz, Sang-Hyeun Park, 2012, Mach. Learn..

Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction

Johannes Fürnkranz, Eneldo Loza Mencía, Camila González, 2017, DS.

Multilabel classification via calibrated label ranking

Eyke Hüllermeier, Johannes Fürnkranz, Klaus Brinker, 2008, Machine Learning.

Efficient prediction algorithms for binary decomposition techniques

Johannes Fürnkranz, Sang-Hyeun Park, 2011, Data Mining and Knowledge Discovery.

Comparing Boosting and Bagging for Decision Trees of Rankings

Johannes Fürnkranz, Eneldo Loza Mencía, Antonella Plaia, 2021, Journal of Classification.

A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems pdf

Johannes Fürnkranz, Martin Müller, Timo Bertram, 2021, ArXiv.

An Empirical Investigation Into Deep and Shallow Rule Learning

Johannes Fürnkranz, Florian Beck, Johannes Fürnkranz, 2021, Frontiers in Artificial Intelligence.

Revisiting Non-Specific Syndromic Surveillance

Johannes Fürnkranz, Eneldo Loza Mencía, Moritz Kulessa, 2021, IDA.

Elliptical Ordinal Embedding

Johannes Fürnkranz, Aïssatou Diallo, 2021, DS.

An Investigation into Mini-Batch Rule Learning pdf

Johannes Fürnkranz, Florian Beck, 2021, ArXiv.

A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance

Johannes Fürnkranz, Eneldo Loza Mencía, Moritz Kulessa, 2021, Comput..

Tree-Based Dynamic Classifier Chains pdf

Johannes Fürnkranz, Moritz Kulessa, Simon Bohlender, 2021, Machine Learning.

Some Chess-Specific Improvements for Perturbation-Based Saliency Maps

Johannes Fürnkranz, Jessica Fritz, 2021, 2021 IEEE Conference on Games (CoG).

Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance

Johannes Fürnkranz, Eneldo Loza Mencía, Moritz Kulessa, 2021, Frontiers in Big Data.

A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance

Johannes Fürnkranz, Eneldo Loza Mencía, Moritz Kulessa, 2021 .

Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking

Johannes Fürnkranz, Martin Müller, Timo Bertram, 2021, 2021 IEEE Conference on Games (CoG).

Structuring Rule Sets Using Binary Decision Diagrams

Johannes Fürnkranz, Phuong Huynh Van Quoc, Florian Beck, 2021, RuleML+RR.

Gradient-based Label Binning in Multi-label Classification pdf

Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, 2021, ECML/PKDD.

Learning Ordinal Embedding from Sets

Johannes Fürnkranz, Aïssatou Diallo, Johannes Fürnkranz, 2021, Entropy.

Beyond DNF: First Steps towards Deep Rule Learning

Johannes Fürnkranz, Florian Beck, 2021, ITAT.

Sum-Product Networks for Early Outbreak Detection of Emerging Diseases

Johannes Fürnkranz, Eneldo Loza Mencía, Moritz Kulessa, 2021, Conference on Artificial Intelligence in Medicine in Europe.

The cultural evolution of age-at-marriage norms

Johannes Fürnkranz, Francesco C. Billari, Alexia Prskawetz, 2002 .

A Study of Probability Estimation Techniques for Rule Learning

Johannes Fürnkranz, Jan-Nikolas Sulzmann, 2009 .

Learning Context-DependentLabel Permutations for Multi-Label Classification

Johannes Fürnkranz, Ruhi Sarikaya, Jinseok Nam, 2019 .

Deep Ordinal Reinforcement Learning

Johannes Fürnkranz, Tobias Joppen, Alexander Zap, 2019, ECML/PKDD.

Evaluation of different Regression Learners under Asymmetric Loss for Predictive Maintenance

Johannes Fürnkranz, Andrei Tolstikov, Frederik Janssen, 2016 .

Proceedings of the ECML/PKDD-08 Workshop on Preference Learning

Eyke Hüllermeier, Johannes Fürnkranz, 2008 .

Informed Hybrid Game Tree Search

Johannes Fürnkranz, Christian Wirth, Tobias Joppen, 2016 .

Determining Factors for Slum Growth with Predictive Data Mining Methods

Johannes Fürnkranz, John Friesen, Lea Rausch, 2018 .

Efficient Pairwise Classification and Ranking

Johannes Fürnkranz, Sang-Hyeun Park, Johannes Fürnkranz, 2007 .

Separate-and-conquer Regression Technical Report TUD – KE – 2010 – 01

Johannes Fürnkranz, Frederik Janssen, Johannes Fürnkranz, 2010 .