Johannes Fürnkranz

68 publications

19 venues

H Index 21

Affiliation

Johannes Kepler University of Linz, Austria
TU Darmstadt, Germany

Links

Name	Venue	Year	citations
Efficient learning of large sets of locally optimal classification rules.	MLJ	2023	0
A flexible class of dependence-aware multi-label loss functions.	MLJ	2022	0
Gradient-Based Label Binning in Multi-label Classification.	ECML/PKDD	2021	0
A review of possible effects of cognitive biases on interpretation of rule-based machine learning models.	Artificial Intelligence	2021	0
Learning Gradient Boosted Multi-label Classification Rules.	ECML/PKDD	2020	0
Permutation Learning via Lehmer Codes.	ECAI	2020	0
On cognitive preferences and the plausibility of rule-based models.	MLJ	2020	0
Learning Context-dependent Label Permutations for Multi-label Classification.	ICML	2019	0
Mending is Better than Ending: Adapting Immutable Classifiers to Nonstationary Environments using Ensembles of Patches.	IJCNN	2019	0
Patching Deep Neural Networks for Nonstationary Environments.	IJCNN	2019	0
Deep Ordinal Reinforcement Learning.	ECML/PKDD	2019	0
Beta Distribution Drift Detection for Adaptive Classifiers.	ESANN	2019	0
Learning Analogy-Preserving Sentence Embeddings for Answer Selection.	CoNLL	2019	0
Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules.	PAKDD	2018	2
Batchwise Patching of Classifiers.	AAAI	2018	3
A Survey of Preference-Based Reinforcement Learning Methods.	JMLR	2017	29
Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification.	NIPS/NeurIPS	2017	33
Model-Free Preference-Based Reinforcement Learning.	AAAI	2016	33
Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization.	CoNLL	2016	7
All-in Text: Learning Document, Label, and Word Representations Jointly.	AAAI	2016	11
Using semantic similarity for multi-label zero-shot classification of text documents.	ESANN	2016	5
What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation.	COLING	2016	2
Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization.	COLING	2016	3
Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning.	ECML/PKDD	2015	8
Editorial.	DMKD	2015	0
Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning.	ECML/PKDD	2014	10
Graded Multilabel Classification by Pairwise Comparisons.	ICDM	2014	3
Large-Scale Multi-label Text Classification - Revisiting Neural Networks.	ECML/PKDD	2014	0
Efficient implementation of class-based decomposition schemes for Naïve Bayes.	MLJ	2014	0
EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning.	ACML	2013	8
Editorial: Preference learning and ranking.	MLJ	2013	2
Preference-based reinforcement learning: a formal framework and a policy iteration algorithm.	MLJ	2012	60
Efficient prediction algorithms for binary decomposition techniques.	DMKD	2012	0
Heuristic Rule-Based Regression via Dynamic Reduction to Classification.	IJCAI	2011	12
Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning.	ECML/PKDD	2011	24
Guest Editorial: Global modeling using local patterns.	DMKD	2010	8
On the quest for optimal rule learning heuristics.	MLJ	2010	0
Efficient voting prediction for pairwise multilabel classification.	ESANN	2009	45
Binary Decomposition Methods for Multipartite Ranking.	ECML/PKDD	2009	42
Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification.	ECML/PKDD	2009	8
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.	SDM	2009	0
Multilabel classification via calibrated label ranking.	MLJ	2008	362
Label ranking by learning pairwise preferences.	Artificial Intelligence	2008	307
Pairwise learning of multilabel classifications with perceptrons.	IJCNN	2008	45
Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain.	ECML/PKDD	2008	62
On Minimizing the Position Error in Label Ranking.	ECML/PKDD	2007	10
On Meta-Learning Rule Learning Heuristics.	ICDM	2007	10
Efficient Pairwise Classification.	ECML/PKDD	2007	64
On Pairwise Naive Bayes Classifiers.	ECML/PKDD	2007	14
Machine learning and games.	MLJ	2006	19
A Unified Model for Multilabel Classification and Ranking.	ECAI	2006	65
ROC 'n' Rule Learning - Towards a Better Understanding of Covering Algorithms.	MLJ	2005	0
An Analysis of Stopping and Filtering Criteria for Rule Learning.	ECML/PKDD	2004	9
Pairwise Preference Learning and Ranking.	ECML/PKDD	2003	137
An Analysis of Rule Evaluation Metrics.	ICML	2003	63
Round Robin Classification.	JMLR	2002	258
Pairwise Classification as an Ensemble Technique.	ECML/PKDD	2002	32
Detecting Temporal Change in Event Sequences: An Application to Demographic Data.	ECML/PKDD	2001	18
Round Robin Rule Learning.	ICML	2001	49
Learning to Use Operational Advice.	ECAI	2000	3
Integrative Windowing.	JAIR	1998	29
Pruning Algorithms for Rule Learning.	MLJ	1997	73
Noise-Tolerant Windowing.	IJCAI	1997	3
Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases.	ECAI	1996	5
A Tight Integration of Pruning and Learning (Extended Abstract).	ECML/PKDD	1995	0
FOSSIL: A Robust Relational Learner.	ECML/PKDD	1994	18
Top-Down Pruning in Relational Learning.	ECAI	1994	9
Incremental Reduced Error Pruning.	ICML	1994	267