Pfahringer, Bernhard

61 publications

ECML-PKDD 2025 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part I Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama

ECML-PKDD 2025 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part II Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama

ECML-PKDD 2025 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part III Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama

ECML-PKDD 2025 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part IV Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama

ECML-PKDD 2025 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part V Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama

ECML-PKDD 2025 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VI Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama

ECML-PKDD 2025 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VII Rita P. Ribeiro, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama

ECML-PKDD 2025 Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VIII Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Rita P. Ribeiro, Inês Dutra, Mykola Pechenizkiy, Paulo Cortez, Sepideh Pashami, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama

ECML-PKDD 2025 Machine Learning for Data Streams with CapyMOA Yibin Sun, Heitor Murilo Gomes, Anton Lee, Nuwan Gunasekara, Guilherme Weigert Cassales, Justin Liu, Marco Heyden, Vítor Cerqueira, Maroua Bahri, Yun Sing Koh, Bernhard Pfahringer, Albert Bifet

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

AutoML 2024 ASML: A Scalable and Efficient AutoML Solution for Data Streams Nilesh Verma, Albert Bifet, Bernhard Pfahringer, Maroua Bahri

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

MLJ 2024 Gradient Boosted Trees for Evolving Data Streams Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet

ECML-PKDD 2024 Leveraging Plasticity in Incremental Decision Trees Marco Heyden, Heitor Murilo Gomes, Edouard Fouché, Bernhard Pfahringer, Klemens Böhm

ICML 2024 Online Isolation Forest Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Giacomo Boracchi

IJCAI 2024 Recurrent Concept Drifts on Data Streams Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet, Yun Sing Koh

IJCAI 2024 Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme Yun Sing Koh, Albert Bifet, Karin R. Bryan, Guilherme Weigert Cassales, Olivier Graffeuille, Nick Jin Sean Lim, Phil Mourot, Ding Ning, Bernhard Pfahringer, Varvara Vetrova, Heitor Murilo Gomes

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

IJCAI 2023 Survey on Online Streaming Continual Learning Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet

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

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

MLJ 2020 An Empirical Analysis of Binary Transformation Strategies and Base Algorithms for Multi-Label Learning Adriano Rivolli, Jesse Read, Carlos Soares, Bernhard Pfahringer, André C. P. L. F. de Carvalho

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

MLJ 2019 Correction to: Adaptive Random Forests for Evolving Data Stream Classification Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem

ACML 2019 Investigating the Effect of Novel Classes in Semi-Supervised Learning Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer

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

MLJ 2018 The Online Performance Estimation Framework: Heterogeneous Ensemble Learning for Data Streams Jan N. van Rijn, Geoffrey Holmes, Bernhard Pfahringer, Joaquin Vanschoren

ECML-PKDD 2018 Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer

MLJ 2017 Adaptive Random Forests for Evolving Data Stream Classification Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem

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

ACML 2016 Learning Distance Metrics for Multi-Label Classification Henry Gouk, Bernhard Pfahringer, Michael Cree

MLOSS 2016 MEKA: A Multi-label/Multi-Target Extension to WEKA Jesse Read, Peter Reutemann, Bernhard Pfahringer, Geoff Holmes

ECML-PKDD 2016 On Dynamic Feature Weighting for Feature Drifting Data Streams Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck, Bernhard Pfahringer, Albert Bifet

MLJ 2015 Evaluation Methods and Decision Theory for Classification of Streaming Data with Temporal Dependence Indre Zliobaite, Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes

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

MLJ 2013 Pairwise Meta-Rules for Better Meta-Learning-Based Algorithm Ranking Quan Sun, Bernhard Pfahringer

ECML-PKDD 2013 Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them Albert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, Geoff Holmes

MLJ 2012 Experiment Databases - A New Way to Share, Organize and Learn from Experiments Joaquin Vanschoren, Hendrik Blockeel, Bernhard Pfahringer, Geoffrey Holmes

MLJ 2012 Scalable and Efficient Multi-Label Classification for Evolving Data Streams Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer

ECML-PKDD 2011 Active Learning with Evolving Streaming Data Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoff Holmes

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

ECML-PKDD 2011 MOA: A Real-Time Analytics Open Source Framework Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl

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

ECML-PKDD 2010 Leveraging Bagging for Evolving Data Streams Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer

MLOSS 2010 MOA: Massive Online Analysis Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer

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

IJCAI 2009 Relational Random Forests Based on Random Relational Rules Grant Anderson, Bernhard Pfahringer

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

ICML 2000 Meta-Learning by Landmarking Various Learning Algorithms Bernhard Pfahringer, Hilan Bensusan, Christophe G. Giraud-Carrier

ECML-PKDD 1997 Compression-Based Pruning of Decision Lists Bernhard Pfahringer

ECML-PKDD 1995 A New MDL Measure for Robust Rule Induction (Extended Abstract) Bernhard Pfahringer

ICML 1995 Compression-Based Discretization of Continuous Attributes Bernhard Pfahringer

ECML-PKDD 1994 Controlling Constructive Induction in CIPF: An MDL Approach Bernhard Pfahringer