Frank, Eibe

37 publications

JMLR 2025 Multiple Instance Verification Xin Xu, Eibe Frank, Geoffrey Holmes

TMLR 2025 Pruning Feature Extractor Stacking for Cross-Domain Few-Shot Learning Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Geoff Holmes

TMLR 2025 Rethinking Memory in Continual Learning: Beyond a Monolithic Store of the past Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet

TMLR 2025 Revisiting Deep Hybrid Models for Out-of-Distribution Detection Paul-Ruben Schlumbom, Eibe Frank

MLJ 2024 Feature Extractor Stacking for Cross-Domain Few-Shot Learning Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes

MLJ 2024 Hitting the Target: Stopping Active Learning at the Cost-Based Optimum Zac Pullar-Strecker, Katharina Dost, Eibe Frank, Jörg Wicker

CoLLAs 2023 Self-Trained Centroid Classifiers for Semi-Supervised Cross-Domain Few-Shot Learning Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes

NeurIPS 2022 A Simple but Strong Baseline for Online Continual Learning: Repeated Augmented Rehearsal Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia

JMLR 2022 Sampling Permutations for Shapley Value Estimation Rory Mitchell, Joshua Cooper, Eibe Frank, Geoffrey Holmes

JAIR 2021 Classifier Chains: A Review and Perspectives Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank

MLJ 2021 Regularisation of Neural Networks by Enforcing Lipschitz Continuity Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael J. Cree

ECML-PKDD 2021 Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality Yunzhe Jia, Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Jin Sean Lim

MLOSS 2019 AffectiveTweets: A Weka Package for Analyzing Affect in Tweets Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer, Saif M. Mohammad

ACML 2019 Stochastic Gradient Trees Henry Gouk, Bernhard Pfahringer, Eibe Frank

ECML-PKDD 2018 MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree

ACML 2017 Probability Calibration Trees Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer

ECML-PKDD 2016 Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection Tim Leathart, Bernhard Pfahringer, Eibe Frank

IJCAI 2015 Positive, Negative, or Neutral: Learning an Expanded Opinion Lexicon from Emoticon-Annotated Tweets Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer

MLJ 2011 Classifier Chains for Multi-Label Classification Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank

ACML 2010 Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees Using Stacking Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer

AAAI 2010 Fast Conditional Density Estimation for Quantitative Structure-Activity Relationships Fabian Buchwald, Tobias Girschick, Eibe Frank, Stefan Kramer

JMLR 2010 WEKA−Experiences with a Java Open-Source Project Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten

ECML-PKDD 2009 Classifier Chains for Multi-Label Classification Jesse Read, Bernhard Pfahringer, Geoffrey Holmes, Eibe Frank

ECML-PKDD 2008 One-Class Classification by Combining Density and Class Probability Estimation Kathryn Hempstalk, Eibe Frank, Ian H. Witten

MLJ 2005 Logistic Model Trees Niels Landwehr, Mark Hall, Eibe Frank

ICML 2004 Ensembles of Nested Dichotomies for Multi-Class Problems Eibe Frank, Stefan Kramer

ECML-PKDD 2003 A Two-Level Learning Method for Generalized Multi-Instance Problems Nils B. Weidmann, Eibe Frank, Bernhard Pfahringer

UAI 2003 Locally Weighted Naive Bayes Eibe Frank, Mark A. Hall, Bernhard Pfahringer

ECML-PKDD 2003 Logistic Model Trees Niels Landwehr, Mark Hall, Eibe Frank

ECML-PKDD 2002 Multiclass Alternating Decision Trees Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall

ECML-PKDD 2001 A Simple Approach to Ordinal Classification Eibe Frank, Mark Hall

MLJ 2000 Naive Bayes for Regression (Technical Note) Eibe Frank, Leonard E. Trigg, Geoffrey Holmes, Ian H. Witten

IJCAI 1999 Domain-Specific Keyphrase Extraction Eibe Frank, Gordon W. Paynter, Ian H. Witten, Carl Gutwin, Craig G. Nevill-Manning

ICML 1999 Making Better Use of Global Discretization Eibe Frank, Ian H. Witten

ICML 1998 Generating Accurate Rule Sets Without Global Optimization Eibe Frank, Ian H. Witten

MLJ 1998 Using Model Trees for Classification Eibe Frank, Yong Wang, Stuart Inglis, Geoffrey Holmes, Ian H. Witten

ICML 1998 Using a Permutation Test for Attribute Selection in Decision Trees Eibe Frank, Ian H. Witten