People


Albert Bifet

Albert Bifet
Institution: 
■ Institut Mines-Telecom
Office: 
48
Groups: 
Former member of the LINCS

Articles

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Evaluation for Regression Analyses on Evolving Data Streams,
Yibin Sun, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet,
CoRR 2025
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CapyMOA: Efficient Machine Learning for Data Streams in Python,
Heitor Murilo Gomes, Anton Lee, Nuwan Gunasekara, Yibin Sun, Guilherme Weigert Cassales, Justin Liu, Marco Heyden, Vitor Cerqueira, Maroua Bahri, Yun Sing Koh, Bernhard Pfahringer, Albert Bifet,
CoRR 2025
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Optimizing Hyperparameters for Quantum Data Re-Uploaders in Calorimetric Particle Identification,
Lea Casse, Bernhard Pfahringer, Albert Bifet, Frederic Magniette,
CoRR 2024
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ASML: A Scalable and Efficient AutoML Solution for Data Streams,
Nilesh Verma, Albert Bifet, Bernhard Pfahringer, Maroua Bahri,
AutoML 2024, Paris, France
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A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams,
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet,
CoRR 2024, Shenzhen, China
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Online Learning of Decision Trees with Thompson Sampling,
Ayman Chaouki, Jesse Read, Albert Bifet,
AISTATS 2024
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Mini-batching with Fused Training and Testing for Data Streams Processing on the Edge,
Reginaldo Luna, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Heitor Murilo Gomes, Hermes Senger,
CF 2024
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Online Isolation Forest,
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Giacomo Boracchi,
ICML 2024
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Recurrent Concept Drifts on Data Streams,
Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet, Yun Sing Koh,
IJCAI 2024
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Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme,
Yun Sing Koh, Albert Bifet, Karin Bryan, Guilherme Weigert Cassales, Olivier Graffeuille, Nick Jin Sean Lim, Phil Mourot, Ding Ning, Bernhard Pfahringer, Varvara Vetrova, Heitor Murilo Gomes,
IJCAI 2024
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Practical Machine Learning for Streaming Data,
Heitor Murilo Gomes, Albert Bifet,
KDD 2024
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Sketch-Based Replay Projection for Continual Learning,
Jack Julian, Yun Sing Koh, Albert Bifet,
KDD 2024
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Adaptive Prediction Interval for Data Stream Regression,
Yibin Sun, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet,
PAKDD 2024
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Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis,
Yibin Sun, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet,
PRICAI 2024
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A Retrospective of the Tutorial on Opportunities and Challenges of Online Deep Learning,
Cedric Kulbach, Lucas Cazzonelli, Hoang Anh Ngo, Minh Huong Le Nguyen, Albert Bifet,
CoRR 2024
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Branches: A Fast Dynamic Programming and Branch & Bound Algorithm for Optimal Decision Trees,
Ayman Chaouki, Jesse Read, Albert Bifet,
CoRR 2024
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Aging and rejuvenating strategies for fading windows in multi-label classification on data streams,
Martha Roseberry, Saso Dzeroski, Albert Bifet, Alberto Cano,
SAC 2023, Talinn, Estonia
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ORSUM 2023 - 6th Workshop on Online Recommender Systems and User Modeling,
João Vinagre, Marie Al Ghossein, Ladislav Peska, Alipio Mario Jorge, Albert Bifet,
RecSys 2023, Singapore, Singapore
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Survey on Online Streaming Continual Learning,
Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet,
IJCAI 2023, Macao, China
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FG\(²\)AN: Fairness-Aware Graph Generative Adversarial Networks,
Zichong Wang, Charles Wallace, Albert Bifet, Xin Yao, Wenbin Zhang,
Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part II 2023, Turin, Italy
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StreamAI: Dealing with Challenges of Continual Learning Systems for Serving AI in Production,
Mariam Barry, Albert Bifet, Jean Luc Billy,
ICSE-SEIP 2023, Melbourne, Australia
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FALL: A Modular Adaptive Learning Platform for Streaming Data,
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet,
ICDE 2023, California, United States
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StreamMLOps: Operationalizing Online Learning for Big Data Streaming & Real-Time Applications,
Mariam Barry, Jacob Montiel, Albert Bifet, Sameer Wadkar, Nikolay Manchev, Max Halford, Raja Chiky, Saad El Jaouhari, Katherine B. Shakman, Joudi Al Fehaily, Fabrice Le Deit, Vinh-Thuy Tran, Eric Guerizec,
39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023 2023, California, United States
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Preventing Discriminatory Decision-making in Evolving Data Streams,
Zichong Wang, Nripsuta Saxena, Tongjia Yu, Sneha Karki, Tyler Zetty, Israat Haque, Shan Zhou, Dukka Kc, Ian Stockwell, Xuyu Wang, Albert Bifet, Wenbin Zhang,
FAccT 2023, Chicago, United States
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Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning,
Anton Lee, Yaqian Zhang, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer,
CIKM 2023, Birmingham (UK), United Kingdom
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Choosing the Right Time to Learn Evolving Data Streams,
Alessio Bernardo, Emanuele Della Valle, Albert Bifet,
IEEE Big Data 2023, Sorrento, Italy
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StreamMLOps: Operationalizing Online Learning for Big Data Streaming & Real-Time Applications,
Mariam Barry, Jacob Montiel, Albert Bifet, Sameer Wadkar, Nikolay Manchev, Max Halford, Raja Chiky, Saad El Jaouhari, Katherine Shakman, Joudi Al Fehaily, Fabrice Le Deit, Vinh Thuy Tran, Eric Guerizec,
ICDE 2023
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FG2AN: Fairness-Aware Graph Generative Adversarial Networks,
Zichong Wang, Charles Wallace, Albert Bifet, Xin Yao, Wenbin Zhang,
ECML/PKDD 2023
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BELLA: Black box model Explanations by Local Linear Approximations,
Nedeljko Radulovic, Albert Bifet, Fabian Suchanek,
CoRR 2023
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Assessing Vulnerability from Its Description,
Zijing Zhang, Vimal Kumar, Michael Mayo, Albert Bifet,
UbiSec 2022, Zhangjiajie, China
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ORSUM 2022 - 5th Workshop on Online Recommender Systems and User Modeling,
João Vinagre, Marie Al Ghossein, Alipio Mario Jorge, Albert Bifet, Ladislav Peska,
RecSys 2022, Seattle (USA), United States
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Repeated Augmented Rehearsal : A simple but strong baseline for online continual learning,
Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia,
Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022 2022, Nouvelle Orleans, United States
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Online Hyperparameter Optimization for Streaming Neural Networks,
Nuwan Gunasekara, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet,
IJCNN 2022, Padua, Italy
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Online Clustering: Algorithms, Evaluation, Metrics, Applications and Benchmarking,
Jacob Montiel, Hoang Anh Ngo, Minh Huong Le Nguyen, Albert Bifet,
KDD 2022, Washington, United States
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Adaptive Model Compression of Ensembles for Evolving Data Streams Forecasting,
Dihia Boulegane, Vitor Cerquiera, Albert Bifet,
IJCNN 2022, Padua, Italy
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Adaptive Online Domain Incremental Continual Learning,
Nuwan Gunasekara, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer,
ICANN 2022, Bristol, United Kingdom
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Adaptive Neural Networks for Online Domain Incremental Continual Learning,
Nuwan Gunasekara, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer,
DS 2022, Montpellier, France
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StreamFlow: A System for Summarizing and Learning Over Industrial Big Data Streams,
Mariam Barry, Saad El Jaouhari, Albert Bifet, Jacob Montiel, Eric Guerizec, Raja Chiky,
IEEE Big Data 2022, Osaka, Japan
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Stream2Graph: Dynamic Knowledge Graph for Online Learning Applied in Large-scale Network,
Mariam Barry, Albert Bifet, Raja Chiky, Saad El Jaouhari, Jacob Montiel, Aissa El Ouafi, Eric Guerizec,
IEEE Big Data 2022, Osaka, Japan
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Continuous Health Monitoring of Machinery using Online Clustering on Unlabeled Data Streams,
Minh Huong Le Nguyen, Fabien Turgis, Pierre Emmanuel Fayemi, Albert Bifet,
IEEE Big Data 2022, Osaka, Japan
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Linear tree shap,
Peng Yu, Albert Bifet, Jesse Read, Chao Xu,
NeurIPS 2022, New Orleans, United States
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Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrences,
Thomas Guyet, Wenbin Zhang, Albert Bifet,
ICCS 2022, London, United Kingdom
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Evolution-Based Online Automated Machine Learning,
Cedric Kulbach, Jacob Montiel, Maroua Bahri, Marco Heyden, Albert Bifet,
PAKDD 2022, Chengdu, China
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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,
NeurIPS 2022
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Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling - ORSUM 2021,
João Vinagre, Alipio Mario Jorge, Marie Al Ghossein, Albert Bifet,
CoRR 2022
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Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrence,
Thomas Guyet, Wenbin Zhang, Albert Bifet,
CoRR 2022
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Green Accelerated Hoeffding Tree,
Eva Garcia Martin, Albert Bifet, Niklas Lavesson, Rikard Konig, Henrik Linusson,
CoRR 2022
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AI Transformation in the Public Sector: Ongoing Research,
Einav Peretz Andersson, Niklas Lavesson, Albert Bifet, Patrick Mikalef,
SAIS 2021, Lulea, Sweden
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Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality,
Yunzhe Jia, Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Jin Sean Lim,
ECML/PKDD 2021, Bilbao, Spain
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ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling,
João Vinagre, Alipio Mario Jorge, Marie Al Ghossein, Albert Bifet,
RecSys 2021, Amsterdam, Netherlands
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FARF: A Fair and Adaptive Random Forests Classifier,
Wenbin Zhang, Albert Bifet, Xiangliang Zhang, Jeremy Weiss, Wolfgang Nejdl,
PAKDD 2021, Virtual, Singapore
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Fast and lightweight binary and multi-branch Hoeffding Tree Regressors,
Saulo Martiello Mastelini, Jacob Montiel, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Andre De Carvalho,
ICDM 2021, Auckland, New Zealand
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Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information,
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet, Russel Pears,
ICDE 2021, Chania, Greece
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Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams,
Maroua Bahri, Albert Bifet,
DS 2021, Halifax, Canada
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S2CE: a hybrid cloud and edge orchestrator for mining exascale distributed streams,
Nicolas Kourtellis, Herodotos Herodotou, Maciej Grzenda, Piotr Wawrzyniak, Albert Bifet,
DEBS 2021, Milan (Italie) Virtuel, Italy
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Kalman Filtering for Learning with Evolving Data Streams,
Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Albert Bifet,
IEEE BigData 2021, Orlando (Floride, Etats-Unis) Virtuel, United States
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Challenges of Machine Learning for Data Streams in the Banking Industry,
Mariam Barry, Albert Bifet, Raja Chiky, Jacob Montiel, Vinh Thuy Tran,
BDA 2021, Virtual, India
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Confident Interpretations of Black Box Classifiers,
Nedeljko Radulovic, Albert Bifet, Fabian Suchanek,
IJCNN 2021, Shenzhen, China
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Model Compression for Dynamic Forecast Combination,
Vitor Cerqueira, Luis Torgo, Carlos Soares, Albert Bifet,
CoRR 2021
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Sketches for Time-Dependent Machine Learning,
Jesus Antonanzas, Marta Arias, Albert Bifet,
CoRR 2021
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Fast Incremental Na\"ıve Bayes with Kalman Filtering,
Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Albert Bifet,
20th International Conference on Data Mining Workshops, ICDM Workshops 2020 2020, Sorrento, Italy
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Performance measures for evolving predictions under delayed labelling classification,
Maciej Grzenda, Heitor Murilo Gomes, Albert Bifet,
IJCNN 2020, Glasgow, United Kingdom
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Adaptive XGBoost for Evolving Data Streams,
Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet,
IJCNN 2020, Glasgow, United Kingdom
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ORSUM 2020- Workshop on Online Recommender Systems and User Modeling,
João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet,
RecSys 2020: Fourteenth ACM Conference on Recommender Systems, Virtual Event, Brazil, September 22-26, 2020 2020, Virtual, Brazil
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Challenges of Stream Learning for Predictive Maintenance in the Railway Sector,
Minh Huong Le Nguyen, Fabien Turgis, Pierre Emmanuel Fayemi, Albert Bifet,
IoT Streams/ITEM@PKDD/ECML 2020, Ghent, Belgium
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confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms,
Matthias Carnein, Heike Trautmann, Albert Bifet, Bernhard Pfahringer,
LION 2020, Athens, Greece
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Randomizing the Self-Adjusting Memory for Enhanced Handling of Concept Drift,
Viktor Losing, Barbara Hammer, Heiko Wersing, Albert Bifet,
IJCNN 2020, Glasgow, United Kingdom
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On Ensemble Techniques for Data Stream Regression,
Heitor Murilo Gomes, Jacob Montiel, Saulo Martiello Mastelini, Bernhard Pfahringer, Albert Bifet,
IJCNN 2020, Glasgow, United Kingdom
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Incremental Rebalancing Learning on Evolving Data Streams,
Alessio Bernardo, Emanuele Della Valle, Albert Bifet,
ICDM 2020, Sorrento, Italy
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Unsupervised Concept Drift Detection Using a Student-Teacher Approach,
Vitor Cerqueira, Heitor Murilo Gomes, Albert Bifet,
DS 2020, thessa, Greece
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Improving parallel performance of ensemble learners for streaming data through data locality with mini-batching,
Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger,
HPCC/DSS/SmartCity 2020, Fiji, Japan
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FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier,
Wenbin Zhang, Albert Bifet,
DS 2020, Tessalonique, Grèce, Greece
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Streaming Time Series Forecasting using Multi-Target Regression with Dynamic Ensemble Selection,
Dihia Boulegane, Albert Bifet, Haytham Elghazel, Giyyarpuram Madhusudan,
IEEE BigData 2020, Atlanta, United States
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AutoML for Stream k-Nearest Neighbors Classification,
Maroua Bahri, Bruno Veloso, Albert Bifet, João Gama,
IEEE BigData 2020, Atlanta, United States
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C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams,
Alessio Bernardo, Heitor Murilo Gomes, Jacob Montiel, Bernhard Pfahringer, Albert Bifet, Emanuele Della Valle,
IEEE BigData 2020, Atlanta, United States
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Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams,
Maroua Bahri, Bernhard Pfahringer, Albert Bifet, Silviu Maniu,
IDA 2020, Konstanz / Virtual, Germany
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Compressed k-Nearest Neighbors Ensembles for Evolving Data Streams,
Maroua Bahri, Albert Bifet, Silviu Maniu, Rodrigo Fernandes De Mello, Nikolaos Tziortziotis,
ECAI 2020, Santiago de Compostella / Virtual, Spain
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CS-ARF: Compressed Adaptive Random Forests for Evolving Data Stream Classification,
Maroua Bahri, Heitor Murilo Gomes, Albert Bifet, Silviu Maniu,
IJCNN 2020, Glasgow / Virtual, United Kingdom
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Survey on Feature Transformation Techniques for Data Streams,
Maroua Bahri, Albert Bifet, Silviu Maniu, Heitor Murilo Gomes,
IJCAI 2020, Yokohama / Virtual, Japan
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Fast Incremental Naïve Bayes with Kalman Filtering,
Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Albert Bifet,
ICDM 2020
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ORSUM - Workshop on Online Recommender Systems and User Modeling,
João Vinagre, Alipio Mario Jorge, Marie Al Ghossein, Albert Bifet,
RecSys 2020
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Emergent and Unspecified Behaviors in Streaming Decision Trees,
Chaitanya Manapragada, Geoffrey Webb, Mahsa Salehi, Albert Bifet,
CoRR 2020
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An Eager Splitting Strategy for Online Decision Trees,
Chaitanya Manapragada, Heitor Murilo Gomes, Mahsa Salehi, Albert Bifet, Geoffrey Webb,
CoRR 2020
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Streaming Random Patches for Evolving Data Stream Classification,
Heitor Murilo Gomes, Jesse Read, Albert Bifet ■,
ICDM 2019, Beijing, China
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Real-Time Machine Learning Competition on Data Streams at the IEEE Big Data 2019,
Dihia Boulegane, Nedeljko Radulovic, Albert Bifet ■, Ghislain Fievet, Jimin Sohn, Yeonwoo Nam, Seojeong Yu, Dong Wan Choi,
IEEE BigData 2019, Los Angeles, United States
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Network of Experts: Learning from Evolving Data Streams Through Network-Based Ensembles,
Heitor Murilo Gomes, Albert Bifet ■, Philippe Fournier Viger, Jones Granatyr, Jesse Read,
ICONIP 2019
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Adaptive Algorithms for Estimating Betweenness and k-path Centralities,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
CIKM 2019, Beijing, France
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Continuous Analytics of Web Streams,
Riccardo Tommasini, Robin Keskisarkka, Jean Paul Calbimonte, Eva Blomqvist, Emanuele Della Valle, Albert Bifet ■,
WWW 2019, San Francisco, United States
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ORSUM 2019 2nd workshop on online recommender systems and user modeling,
João Vinagre, Alipio Mario Jorge, Albert Bifet ■, Marie Al Ghossein,
RecSys 2019, Copenhagen, France
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Metropolis-Hastings Algorithms for Estimating Betweenness Centrality Talel Abdessalem,
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet ■,
22nd International Conference on Extending Database Technology EDBT 2019 2019, Lisbon, Portugal
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Adaptive Random Forests with Resampling for Imbalanced data Streams,
Luis Eduardo Boiko Ferreira, Heitor Murilo Gomes, Albert Bifet ■, Luiz Oliveira,
IJCNN 2019, Budapest, France
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Arbitrated Dynamic Ensemble with Abstaining for Time-Series Forecasting on Data Streams,
Dihia Boulegane, Albert Bifet ■, Giyyarpuram Madhusudan,
IEEE BigData 2019
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Feature Scoring using Tree-Based Ensembles for Evolving Data Streams,
Heitor Murilo Gomes, Rodrigo Fernandes De Mello, Bernhard Pfahringer, Albert Bifet ■,
IEEE BigData 2019
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Semi-supervised Learning over Streaming Data using MOA,
Minh Huong Le Nguyen, Heitor Murilo Gomes, Albert Bifet ■,
IEEE BigData 2019
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Metropolis-Hastings Algorithms for Estimating Betweenness Centrality,
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet ■,
EDBT 2019
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Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets,
Albert Bifet ■, Barbara Hammer, Frank Michael Schleif,
ESANN 2019
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IDSA-IoT: An Intrusion Detection System Architecture for IoT Networks,
Guilherme Weigert Cassales, Hermes Senger, Elaine Ribeiro De Faria, Albert Bifet ■,
ISCC 2019
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Towards Automated Configuration of Stream Clustering Algorithms,
Matthias Carnein, Heike Trautmann, Albert Bifet ■, Bernhard Pfahringer,
PKDD/ECML Workshops 2019
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Resource-aware Elastic Swap Random Forest for Evolving Data Streams,
Diego Marrón, Eduard Ayguade, Jose Ramon Herrero, Albert Bifet ■,
CoRR 2019
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Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning,
Jesus Lobo, Izaskun Oregi, Albert Bifet ■, Javier Del Ser,
CoRR 2019
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Rebalancing Learning on Evolving Data Streams,
Alessio Bernardo, Emanuele Della Valle, Albert Bifet ■,
CoRR 2019
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A Sketch-Based Naive Bayes Algorithms for Evolving Data Streams,
Maroua Bahri, Silviu Maniu, Albert Bifet ■,
IEEE BigData 2018, Seattle, United States
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Learning Fast and Slow: A Unified Batch/Stream Framework,
Jacob Montiel, Albert Bifet ■, Viktor Losing, Jesse Read, Talel Abdessalem,
IEEE BigData 2018, Seattle, United States
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DyBED: An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
IEEE BigData 2018, Seattle, United States
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An In-depth Comparison of Group Betweenness Centrality Estimation Algorithms,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
IEEE BigData 2018, Seattle, United States
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Unsupervised real-time detection of BGP anomalies leveraging high-rate and fine-grained telemetry data,
Andrian Putina ■, Steven Barth, Albert Bifet ■, Drew Pletcher, Cristina Precup, Patrice Nivaggioli, Dario Rossi ■,
INFOCOM Workshops 2018, Honolulu, United States
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Adaptive random forests for data stream regression,
Heitor Murilo Gomes, Jean Paul Barddal, Luis Eduardo Boiko Ferreira, Albert Bifet ■,
ESANN 2018, Bruges, Belgium
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Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
PAKDD 2018, Melbourne, Australia
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Scalable Model-Based Cascaded Imputation of Missing Data,
Jacob Montiel, Jesse Read, Albert Bifet ■, Talel Abdessalem,
PAKDD 2018, Melbourne, Australia
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Ubiquitous Artificial Intelligence and Dynamic Data Streams,
Albert Bifet ■, Jesse Read,
DEBS 2018, Hamilton, New Zealand
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Telemetry-based stream-learning of BGP anomalies,
Andrian Putina ■, Dario Rossi ■, Albert Bifet ■, Steven Barth, Drew Pletcher, Cristina Precup, Patrice Nivaggioli,
Big-DAMA@SIGCOMM 2018, Budapest, Hungary
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EXAD: A System for Explainable Anomaly Detection on Big Data Traces,
Fei Song, Yanlei Diao, Jesse Read, Arnaud Stiegler, Albert Bifet ■,
ICDM Workshops 2018, Singapore, Singapore
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Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders,
Tian Guo, Albert Bifet ■, Nino Antulov Fantulin,
ICDM 2018
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Large-Scale Learning from Data Streams with Apache SAMOA,
Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet ■,
CoRR 2018
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Novel Adaptive Algorithms for Estimating Betweenness, Coverage and k-path Centralities,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
CoRR 2018
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Droplet Ensemble Learning on Drifting Data Streams,
Pierre Xavier Loeffel, Albert Bifet ■, Christophe Marsala, Marcin Detyniecki,
IDA 2017, Londres, United Kingdom
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Internet of Things (IoT) Analytics,
Albert Bifet ■,
The 16th International Conference on Artificial Intelligence and Soft Computing ICAISC 2017 2017, Zakopane, Poland
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Low-latency multi-threaded ensemble learning for dynamic big data streams,
Diego Marron, Eduard Ayguade, Jose Herrero, Jesse Read, Albert Bifet ■,
IEEE BigData 2017, Boston, France
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Predicting over-indebtedness on batch and streaming data,
Jacob Montiel, Albert Bifet ■, Talel Abdessalem,
IEEE BigData 2017
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Extremely Fast Decision Tree Mining for Evolving Data Streams,
Albert Bifet ■, Jiajin Zhang, Wei Fan, Cheng He, Jianfeng Zhang, Jianfeng Qian, Geoff Holmes, Bernhard Pfahringer,
KDD 2017
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Inferring Demographics and Social Networks of Mobile Device Users on Campus From AP-Trajectories,
Pinghui Wang, Feiyang Sun, Di Wang, Jing Tao, Xiaohong Guan, Albert Bifet ■,
WWW 2017
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Metropolis-Hastings Algorithms for Estimating Betweenness Centrality in Large Networks,
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet ■,
CoRR 2017
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Discriminative Distance-Based Network Indices and the Tiny-World Property,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
CoRR 2017
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Massive Online Analytics for the Internet of Things (IoT),
Albert Bifet,
The 8th Asian Conference on Machine Learning 2016, Hamilton, New Zealand
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Echo State Hoeffding Tree Learning,
Diego Marron, Jesse Read, Albert Bifet, Talel Abdessalem, Eduard Ayguade, Jose Herrero,
ACML 2016
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VHT: Vertical hoeffding tree,
Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet, Arinto Murdopo,
IEEE BigData 2016
⇣
IoT Big Data Stream Mining,
Gianmarco De Francisci Morales, Albert Bifet, Latifur Khan, João Gama, Wei Fan,
KDD 2016
⇣
On Dynamic Feature Weighting for Feature Drifting Data Streams,
Jean Paul Barddal, Heitor Murilo Gomes, Fabricio Enembreck, Bernhard Pfahringer, Albert Bifet,
ECML/PKDD 2016
⇣
Deferral classification of evolving temporal dependent data streams,
Michael Mayo, Albert Bifet,
SAC 2016
⇣
Analyzing Big Data Streams with Apache SAMOA,
Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet,
MSM@WWW,MUSE@PKDD/ECML 2016
⇣
⇣
StreamDM: Advanced Data Mining in Spark Streaming,
Albert Bifet, Silviu Maniu, Jianfeng Qian, Guangjian Tian, Cheng He, Wei Fan,
ICDM Workshops 2015, Atlantic City, NJ, United States
⇣
Use of ensembles of Fourier spectra in capturing recurrent concepts in data streams,
Sripirakas Sakthithasan, Russel Pears, Albert Bifet, Bernhard Pfahringer,
IJCNN 2015
⇣
Efficient Online Evaluation of Big Data Stream Classifiers,
Albert Bifet, Gianmarco De Francisci Morales, Jesse Read, Geoff Holmes, Bernhard Pfahringer,
KDD 2015
⇣
Preface,
Wei Fan, Albert Bifet, Qiang Yang, Philip Yu,
BigMine 2015
⇣
Drift Detection Using Stream Volatility,
David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet,
ECML/PKDD 2015
⇣
Deep learning in partially-labeled data streams,
Jesse Read, Fernando Perez Cruz, Albert Bifet,
SAC 2015
⇣
Change detection in categorical evolving data streams Détection des changement dans des flots de données qualitatives,
Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet,
SAC 2014 - 29th Annual ACM Symposium on Applied Computing 2014, Gyeongju, Korea, Republic of
⇣
Détection de changements dans des flots de données qualitatives Change detection in categorical evolving data streams,
Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet,
14e Journées Internationales Francophones sur l'Extraction et la Gestion des Connaissances (EGC) 2014, Rennes, France
⇣
Distributed Adaptive Model Rules for mining big data streams,
Anh Thu Vu, Gianmarco De Francisci Morales, João Gama, Albert Bifet,
IEEE BigData 2014
⇣
Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams,
Diego Marron, Albert Bifet, Gianmarco De Francisci Morales,
ECAI 2014
⇣
Détection de changements dans des flots de données qualitatives,
Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet,
EGC 2014
⇣
Big Data Stream Learning with SAMOA,
Albert Bifet, Gianmarco De Francisci Morales,
ICDM Workshops 2014
⇣
Incremental Ensemble Classifier Addressing Non-stationary Fast Data Streams,
Brandon Parker, Latifur Khan, Albert Bifet,
ICDM Workshops 2014
⇣
Multi-label Classification with Meta-Labels,
Jesse Read, Antti Puurula, Albert Bifet,
ICDM 2014
⇣
Change detection in categorical evolving data streams,
Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet,
SAC 2014
⇣
Kaggle LSHTC4 Winning Solution,
Antti Puurula, Jesse Read, Albert Bifet,
CoRR 2014
⇣
Clustering based active learning for evolving data streams Apprentissage actif sur flux des données basé sur clustering,
Dino Ienco, Albert Bifet, I. Zliobaite, B. Pfahringer,
Discovery Science 2013, Singapour, Singapore
⇣
Clustering Based Active Learning for Evolving Data Streams,
Dino Ienco, Albert Bifet, Indre Zliobaite, Bernhard Pfahringer,
Discovery Science 2013
⇣
CD-MOA: Change Detection Framework for Massive Online Analysis,
Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes, Indre Zliobaite,
IDA 2013
⇣
STRIP: stream learning of influence probabilities,
Konstantin Kutzkov, Albert Bifet, Francesco Bonchi, Aristides Gionis,
KDD 2013
⇣
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them,
Albert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, Geoff Holmes,
ECML/PKDD 2013
⇣
Efficient data stream classification via probabilistic adaptive windows,
Albert Bifet, Bernhard Pfahringer, Jesse Read, Geoff Holmes,
SAC 2013
⇣
Stream Data Mining Using the MOA Framework,
Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read,
DASFAA 2012
⇣
Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data,
Jesse Read, Albert Bifet, Bernhard Pfahringer, Geoff Holmes,
IDA 2012
⇣
MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer,
Discovery Science 2011
⇣
Online Evaluation of Email Streaming Classifiers Using GNUsmail,
Jose Carmona Cejudo, Manuel Baena Garcia, Jose Del Campo Avila, Albert Bifet, João Gama, Rafael Morales Bueno,
IDA 2011
⇣
Mining frequent closed graphs on evolving data streams,
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Ricard Gavalda,
KDD 2011
⇣
An effective evaluation measure for clustering on evolving data streams,
Hardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
KDD 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,
ECML/PKDD 2011
⇣
Active Learning with Evolving Streaming Data,
Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoff Holmes,
ECML/PKDD 2011
⇣
Detecting Sentiment Change in Twitter Streaming Data,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Ricard Gavalda,
WAPA 2011
⇣
Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classification,
Jose Carmona Cejudo, Manuel Baena Garcia, Rafael Morales Bueno, João Gama, Albert Bifet,
WAPA 2011
⇣
Streaming Multi-label Classification,
Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
WAPA 2011
⇣
MOA Concept Drift Active Learning Strategies for Streaming Data,
Indre Zliobaite, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
WAPA 2011
⇣
Sentiment Knowledge Discovery in Twitter Streaming Data,
Albert Bifet, Eibe Frank,
Discovery Science 2010
⇣
GNUsmail: Open Framework for On-line Email Classification,
Jose Carmona Cejudo, Manuel Baena Garcia, Jose Del Campo Avila, Rafael Morales Bueno, Albert Bifet,
ECAI 2010
⇣
Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA,
Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
ICDM Workshops 2010
⇣
Fast Perceptron Decision Tree Learning from Evolving Data Streams,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Eibe Frank,
PAKDD 2010
⇣
Leveraging Bagging for Evolving Data Streams,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer,
ECML/PKDD 2010
⇣
Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking,
Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer,
ACML 2010
⇣
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering,
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl,
WAPA 2010
⇣
Improving Adaptive Bagging Methods for Evolving Data Streams,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Ricard Gavalda,
ACML 2009
⇣
Adaptive Learning from Evolving Data Streams,
Albert Bifet, Ricard Gavalda,
IDA 2009
⇣
New ensemble methods for evolving data streams,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Ricard Gavalda,
KDD 2009
⇣
Adaptive XML Tree Classification on Evolving Data Streams,
Albert Bifet, Ricard Gavalda,
ECML/PKDD 2009
⇣
Mining Implications from Lattices of Closed Trees,
Jose Balcazar, Albert Bifet, Antoni Lozano,
EGC 2008
⇣
Mining adaptively frequent closed unlabeled rooted trees in data streams,
Albert Bifet, Ricard Gavalda,
KDD 2008
⇣
Subtree Testing and Closed Tree Mining Through Natural Representations,
Jose Balcazar, Albert Bifet, Antoni Lozano,
DEXA Workshops 2007
⇣
Mining Frequent Closed Unordered Trees Through Natural Representations,
Jose Balcazar, Albert Bifet, Antoni Lozano,
ICCS 2007
⇣
Learning from Time-Changing Data with Adaptive Windowing,
Albert Bifet, Ricard Gavalda,
SDM 2007
⇣
Kalman Filters and Adaptive Windows for Learning in Data Streams,
Albert Bifet, Ricard Gavalda,
Discovery Science 2006
⇣
An Analysis of Factors Used in Search Engine Ranking,
Albert Bifet, Carlos Castillo, Paul Alexandru Chirita, Ingmar Weber,
AIRWeb 2005

Journal articles

⇣
A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study,
Guilherme Weigert Cassales, Serajis Salekin, Nick Jin Sean Lim, Dean Meason, Albert Bifet, Bernhard Pfahringer, Eibe Frank,
Ecol. Informatics 2025
⇣
Ai-enabled automated common vulnerability scoring from common vulnerabilities and exposures descriptions,
Zijing Zhang, Vimal Kumar, Bernhard Pfahringer, Albert Bifet,
Int. J. Inf. Sec. 2025
⇣
NFA: A neural factorization autoencoder based online telephony fraud detection,
Abdul Wahid, Mounira Msahli, Albert Bifet, Gérard Memmi ■,
Digit. Commun. Networks 2024
⇣
Machine Learning (In) Security: A Stream of Problems,
Fabricio Ceschin, Marcus Botacin, Albert Bifet, Bernhard Pfahringer, Luiz Oliveira, Heitor Murilo Gomes, Andre Gregio,
DTRAP 2024
⇣
Gradient boosted trees for evolving data streams,
Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet,
Mach. Learn. 2024
⇣
⇣
A Survey on Semi-supervised Learning for Delayed Partially Labelled Data Streams,
Heitor Murilo Gomes, Maciej Grzenda, Rodrigo Fernandes De Mello, Jesse Read, Minh Huong Le Nguyen, Albert Bifet,
ACM Computing Surveys 2023
⇣
⇣
Editorial: Seventh special issue on Knowledge Discovery and Business Intelligence,
Paulo Cortez, Albert Bifet,
Expert Systems 2023
⇣
⇣
teex: A toolbox for the evaluation of explanations,
Jesus Antonanzas, Yunzhe Jia, Eibe Frank, Albert Bifet, Bernhard Pfahringer,
Neurocomputing 2023
⇣
⇣
Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing,
Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger,
IEEE Transactions on Network and Service Management 2023
⇣
⇣
Combining Diverse Meta-Features to Accurately Identify Recurring Concept Drift in Data Streams,
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet,
ACM Transactions on Knowledge Discovery from Data (TKDD) 2023
⇣
⇣
STUDD: a student-teacher method for unsupervised concept drift detection,
Vitor Cerqueira, Heitor Murilo Gomes, Albert Bifet, Luis Torgo,
Machine Learning 2023
⇣
⇣
Wangiri Fraud: Pattern Analysis and Machine-Learning-Based Detection,
Akshaya Ravi, Mounira Msahli, Han Qiu, Gérard Memmi ■, Albert Bifet, Meikang Qiu,
IEEE Internet of Things Journal 2023
⇣
⇣
Exploring the potentials of online machine learning for predictive maintenance: a case study in the railway industry,
Minh Huong Le Nguyen, Fabien Turgis, Pierre Emmanuel Fayemi, Albert Bifet,
Applied Intelligence 2023
⇣
Towards time-evolving analytics: Online learning for time-dependent evolving data streams,
Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Vitor Cerqueira, Albert Bifet,
Data Sci. 2023
⇣
⇣
Resource-Aware Edge-Based Stream Analytics,
Ioan Petri, Ioan Chirila, Heitor Murilo Gomes, Albert Bifet, Omer Rana,
IEEE Internet Computing 2022
⇣
⇣
Analyzing and repairing concept drift adaptation in data stream classification,
Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson,
Mach. Learn. 2022, Porto, Portugal
⇣
⇣
Preface to the special issue on dynamic recommender systems and user models,
João Vinagre, Alipio Mario Jorge, Marie Al Ghossein, Albert Bifet, Paolo Cremonesi,
User Modeling and User-Adapted Interaction 2022
⇣
⇣
TA4L: Efficient temporal abstraction of multivariate time series,
Natalia Mordvanyuk, Beatriz López, Albert Bifet,
Knowledge-Based Systems 2022
⇣
⇣
LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding,
Emanuele Pio Barracchia, Gianvito Pio, Albert Bifet, Heitor Murilo Gomes, Bernhard Pfahringer, Michelangelo Ceci,
Information Sciences 2022
⇣
⇣
SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams,
Yibin Sun, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet,
Data Mining and Knowledge Discovery 2022
⇣
⇣
VEPRECO: Vertical databases with pre-pruning strategies and common candidate selection policies to fasten sequential pattern mining,
Natalia Mordvanyuk, Albert Bifet, Beatriz López,
Expert Systems with Applications 2022
⇣
⇣
An eager splitting strategy for online decision trees in ensembles,
Chaitanya Manapragada, Heitor Murilo Gomes, Mahsa Salehi, Albert Bifet, Geoffrey Webb,
Data Mining and Knowledge Discovery 2022
⇣
⇣
A Survey on Spatio-temporal Data Analytics Systems,
Mahbub Alam, Luis Torgo, Albert Bifet,
ACM Computing Surveys 2022
⇣
⇣
Open challenges for Machine Learning based Early Decision-Making research,
Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clerot, Antoine Cornuejols, João Gama, Georges Hebrail, Vincent Lemaire, Pierre Francois Marteau,
SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining 2022
⇣
⇣
Energy modeling of Hoeffding tree ensembles,
Eva Garcia Martin, Albert Bifet, Niklas Lavesson,
Intelligent Data Analysis 2021
⇣
⇣
Learning from evolving data streams through ensembles of random patches,
Heitor Murilo Gomes, Jesse Read, Albert Bifet, Robert Durrant,
Knowledge and Information Systems (KAIS) 2021
⇣
⇣
River: machine learning for streaming data in Python,
Jacob Montiel, Max Halford, Saulo Martiello Mastelini, Geoffrey Bolmier, Raphael Sourty, Robin Vaysse, Adil Zouitine, Heitor Murilo Gomes, Jesse Read, Talel Abdessalem, Albert Bifet,
Journal of Machine Learning Research 2021
⇣
⇣
Improving the performance of bagging ensembles for data streams through mini-batching,
Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger,
Information Sciences 2021
⇣
⇣
vertTIRP: Robust and efficient vertical frequent time interval-related pattern mining,
Natalia Mordvanyuk, Beatriz López, Albert Bifet,
Expert Systems with Applications 2021
⇣
⇣
Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs,
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem,
Fundamenta Informaticae 2021
⇣
⇣
Binding data mining and expert knowledge for one-day-ahead prediction of hourly global solar radiation,
Jose Del Campo Avila, Abdelatif Takilalte, Albert Bifet, Llanos Mora López,
Expert Systems with Applications 2021
⇣
⇣
CURIE: a cellular automaton for concept drift detection,
Jesus Lobo, Javier Del Ser, Eneko Osaba, Albert Bifet, Francisco Herrera,
Data Mining and Knowledge Discovery 2021
⇣
⇣
Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency,
Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet,
Data Mining and Knowledge Discovery 2021
⇣
⇣
Data stream analysis: Foundations, major tasks and tools,
Maroua Bahri, Albert Bifet, João Gama, Heitor Murilo Gomes, Silviu Maniu,
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2021
⇣
⇣
Fifth special issue on knowledge discovery and business intelligence,
Paulo Cortez, Albert Bifet,
Expert Systems 2020
⇣
⇣
Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning,
Jesus Lobo, Izaskun Oregi, Albert Bifet, Javier Del Ser,
Neural Networks 2020
⇣
⇣
Sampling informative patterns from large single networks,
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet, Meriem Bouzbila,
Future Generation Computer Systems 2020
⇣
⇣
Discriminative Streaming Network Embedding,
Yiyan Qi, Jiefeng Cheng, Xiaojun Chen, Reynold Cheng, Albert Bifet, Pinghui Wang,
Knowledge-Based Systems 2020
⇣
⇣
IoT data stream analytics,
Albert Bifet, João Gama,
Annals of Telecommunications - annales des télécommunications 2020
⇣
⇣
Delayed labelling evaluation for data streams,
Maciej Grzenda, Heitor Murilo Gomes, Albert Bifet,
Data Mining and Knowledge Discovery 2020
⇣
⇣
Spiking Neural Networks and online learning: An overview and perspectives,
Jesus Lobo, Javier Del Ser, Albert Bifet, Nikola Kasabov,
Neural Networks 2020
⇣
⇣
SCALAR - A Platform for Real-time Machine Learning Competitions on Data Streams,
Nedeljko Radulovic, Dihia Boulegane, Albert Bifet,
Journal of Open Source Software 2020
⇣
⇣
Introduction to the special issue on Big Data, IoT Streams and Heterogeneous Source Mining,
Jesse Read, Albert Bifet ■, Wei Fan, Qiang Yang, Philip Yu,
International Journal of Data Science and Analytics 2019
⇣
⇣
Recurring concept meta-learning for evolving data streams,
Robert Anderson, Yun Sing Koh, Gillian Dobbie, Albert Bifet ■,
Expert Systems with Applications 2019
⇣
⇣
Boosting decision stumps for dynamic feature selection on data streams,
Jean Paul Barddal, Fabricio Enembreck, Heitor Murilo Gomes, Albert Bifet ■, Bernhard Pfahringer,
Information Systems 2019
⇣
Machine learning for streaming data,
Heitor Murilo Gomes, Jesse Read, Albert Bifet ■, Jean Paul Barddal, João Gama,
SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining 2019
⇣
⇣
Efficient frequent subgraph mining on large streaming graphs,
Abhik Ray, Lawrence Holder, Albert Bifet ■,
Intelligent Data Analysis 2019
⇣
⇣
Measuring the Shattering coefficient of Decision Tree models,
Rodrigo Fernandes De Mello, Chaitanya Manapragada, Albert Bifet ■,
Expert Systems with Applications 2019
⇣
⇣
On learning guarantees to unsupervised concept drift detection on data streams,
Rodrigo Fernandes De Mello, Yule Vaz, Carlos Henrique Grossi Ferreira, Albert Bifet ■,
Expert Systems with Applications 2019
⇣
⇣
Merit-guided dynamic feature selection filter for data streams,
Jean Paul Barddal, Fabricio Enembreck, Heitor Murilo Gomes, Albert Bifet ■, Bernhard Pfahringer,
Expert Syst. Appl. 2019
⇣
Correction to: Adaptive random forests for evolving data stream classification,
Heitor Murilo Gomes, Albert Bifet ■, Jesse Read, Jean Paul Barddal, Fabricio Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem,
Mach. Learn. 2019
⇣
Machine learning for streaming data: state of the art, challenges, and opportunities,
Heitor Murilo Gomes, Jesse Read, Albert Bifet ■, Jean Paul Barddal, João Gama,
SIGKDD Explor. 2019
⇣
⇣
Discriminative Distance-Based Network Indices with Application to Link Prediction,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
The Computer Journal 2018
⇣
⇣
Scikit-Multiflow: A Multi-output Streaming Framework,
Jacob Montiel, Jesse Read, Albert Bifet ■, Talel Abdessalem,
Journal of Machine Learning Research 2018
⇣
Predicting attributes and friends of mobile users from AP-Trajectories,
Pinghui Wang, Feiyang Sun, Di Wang, Jing Tao, Xiaohong Guan, Albert Bifet ■,
Inf. Sci. 2018
⇣
⇣
Adaptive random forests for evolving data stream classification,
Heitor Murilo Gomes, Albert Bifet ■, Jesse Read, Jean Paul Barddal, Fabricio Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem,
Machine Learning 2017
⇣
⇣
Data stream classification using random feature functions and novel method combinations,
Diego Marron, Jesse Read, Albert Bifet ■, Nacho Navarro,
Journal of Systems and Software 2017
⇣
⇣
A Survey on Ensemble Learning for Data Stream Classification,
Heitor Murilo Gomes, Jean Paul Barddal, Fabricio Enembreck, Albert Bifet ■,
ACM Computing Surveys 2017
⇣
A streaming flow-based technique for traffic classification applied to 12 + 1 years of Internet traffic,
Valentin Carela Español, Pere Barlet Ros, Albert Bifet, Kensuke Fukuda,
Telecommun. Syst. 2016
⇣
Adaptive Model Rules From High-Speed Data Streams,
João Duarte, João Gama, Albert Bifet,
ACM Trans. Knowl. Discov. Data 2016
⇣
An efficient closed frequent itemset miner for the MOA stream mining system,
Massimo Quadrana, Albert Bifet, Ricard Gavalda,
AI Commun. 2015
⇣
SAMOA: scalable advanced massive online analysis,
Gianmarco De Francisci Morales, Albert Bifet,
J. Mach. Learn. Res. 2015
⇣
Evaluation methods and decision theory for classification of streaming data with temporal dependence,
Indre Zliobaite, Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes,
Mach. Learn. 2015
⇣
A survey on concept drift adaptation,
João Gama, Indre Zliobaite, Albert Bifet, Mykola Pechenizkiy, Abdelhamid Bouchachia,
ACM Comput. Surv. 2014
⇣
Active Learning With Drifting Streaming Data,
Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoffrey Holmes,
IEEE Trans. Neural Networks Learn. Syst. 2014
⇣
Scalable and efficient multi-label classification for evolving data streams,
Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
Mach. Learn. 2012
⇣
Mining big data: current status, and forecast to the future,
Wei Fan, Albert Bifet,
SIGKDD Explor. 2012
⇣
Next challenges for adaptive learning systems,
Indre Zliobaite, Albert Bifet, Mohamed Medhat Gaber, Bogdan Gabrys, João Gama, Leandro Minku, Katarzyna Musial,
SIGKDD Explor. 2012
⇣
Ensembles of Restricted Hoeffding Trees,
Albert Bifet, Eibe Frank, Geoff Holmes, Bernhard Pfahringer,
ACM Trans. Intell. Syst. Technol. 2012
⇣
Mining frequent closed trees in evolving data streams,
Albert Bifet, Ricard Gavalda,
Intell. Data Anal. 2011
⇣
MOA: Massive Online Analysis,
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer,
J. Mach. Learn. Res. 2010
⇣
Mining frequent closed rooted trees,
Jose Balcazar, Albert Bifet, Antoni Lozano,
Mach. Learn. 2010

Editorships

⇣
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part I,
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part X,
Albert Bifet, Tomas Krilavicius, Ioanna Miliou, Slawomir Nowaczyk,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part II,
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part III,
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IV,
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part V,
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VI,
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VII,
Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VIII,
Albert Bifet, Povilas Daniusis, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Kai Puolamaki, Indre Zliobaite,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IX,
Albert Bifet, Tomas Krilavicius, Ioanna Miliou, Slawomir Nowaczyk,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2024
⇣
Discovery Science - 26th International Conference, DS 2023, Porto, Portugal, October 9-11, 2023, Proceedings,
Albert Bifet, Ana Carolina Lorena, Rita Ribeiro, João Gama, Pedro Abreu,
['DS', 'Lecture Notes in Computer Science'] 2023
⇣
Proceedings of the 6th Workshop on Online Recommender Systems and User Modeling co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 19th, 2023,
João Vinagre, Marie Al Ghossein, Ladislav Peska, Alipio Mario Jorge, Albert Bifet,
['ORSUM@RecSys', 'CEUR Workshop Proceedings'] 2023
⇣
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I,
Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Froning, Francesco Gullo, Pedro Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita Ribeiro, Ricard Gavalda, Elio Masciari, Zbigniew Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Iberia Medeiros, Guilherme Graca, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami,
['PKDD/ECML Workshops', 'Communications in Computer and Information Science'] 2023
⇣
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II,
Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Froning, Francesco Gullo, Pedro Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita Ribeiro, Ricard Gavalda, Elio Masciari, Zbigniew Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Iberia Medeiros, Guilherme Graca, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami,
['PKDD/ECML Workshops', 'Communications in Computer and Information Science'] 2023
⇣
Proceedings of the 5th Workshop on Online Recommender Systems and User Modeling co-located with the 16th ACM Conference on Recommender Systems, ORSUM@RecSys 2022, Seattle, WA, USA, September 23rd, 2022,
João Vinagre, Marie Al Ghossein, Alipio Mario Jorge, Albert Bifet, Ladislav Peska,
['ORSUM@RecSys', 'CEUR Workshop Proceedings'] 2022
⇣
Proceedings of the 8th International Workshop on Big Data, IoT Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications co-located with 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, Alaska, August 4-8, 2019,
Albert Bifet, Michele Berlingerio, João Gama, Jesse Read, Ana Rita Nogueira,
['BigMine@KDD', 'CEUR Workshop Proceedings'] 2020
⇣
IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning - Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Revised Selected Papers,
João Gama, Sepideh Pashami, Albert Bifet, Moamar Sayed Mouchaweh, Holger Froning, Franz Pernkopf, Gregor Schiele, Michaela Blott,
['IoT Streams/ITEM@PKDD/ECML', 'Communications in Computer and Information Science'] 2020
⇣
Proceedings of the 3rd Workshop on Online Recommender Systems and User Modeling co-located with the 14th ACM Conference on Recommender Systems (RecSys 2020), Virtual Event, September 25, 2020,
João Vinagre, Alipio Mario Jorge, Marie Al Ghossein, Albert Bifet,
['ORSUM@RecSys', 'CEUR Workshop Proceedings'] 2020
⇣
ECML PKDD 2018 Workshops - DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers,
Anna Monreale, Carlos Alzate, Michael Kamp, Yamuna Krishnamurthy, Daniel Paurat, Moamar Sayed Mouchaweh, Albert Bifet ■, João Gama, Rita Ribeiro,
['DMLE/IOTSTREAMING@PKDD/ECML', 'Communications in Computer and Information Science'] 2019
⇣
ECML PKDD 2018 Workshops - Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings,
Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet ■, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva Garcia Martin, Ricard Gavalda, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian Molloy, Maria Irina Nicolae, Mathieu Sinn,
['Nemesis/UrbReas/SoGood/IWAISe/GDM@PKDD/ECML', 'Lecture Notes in Computer Science'] 2019
⇣
2nd Workshop on Online Recommender Systems and User Modeling, ORSUM@RecSys 2019, 19 September 2019, Copenhagen, Denmark,
João Vinagre, Alipio Mario Jorge, Albert Bifet ■, Marie Al Ghossein,
['ORSUM@RecSys', 'Proceedings of Machine Learning Research'] 2019
⇣
Streaming Data Mining with Massive Online Analytics (MOA),
Albert Bifet ■, Jesse Read, Geoff Holmes, Bernhard Pfahringer,
2018
⇣
Proceedings of the Workshop on IoT Large Scale Learning from Data Streams co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18-22, 2017,
Moamar Sayed Mouchaweh, Albert Bifet ■, Hamid Bouchachia, João Gama, Rita Paula Ribeiro,
['IOTSTREAMING@PKDD/ECML', 'CEUR Workshop Proceedings'] 2017
⇣
Proceedings of the 5th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2016, San Francisco, CA, USA, August 14, 2016,
Wei Fan, Albert Bifet, Jesse Read, Qiang Yang, Philip Yu,
['BigMine', 'JMLR Workshop and Conference Proceedings'] 2016
⇣
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III,
Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou,
['ECML/PKDD', 'Lecture Notes in Computer Science'] 2015
⇣
Proceedings of the 3rd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2014, New York City, USA, August 24, 2014,
Wei Fan, Albert Bifet, Qiang Yang, Philip Yu,
['BigMine', 'JMLR Workshop and Conference Proceedings'] 2014
⇣
Proceedings of the 2nd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2013, Chicago, IL, USA, August 11, 2013,
Wei Fan, Albert Bifet, Qiang Yang, Philip Yu,
BigMine 2013
⇣
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2012, Beijing, China, August 12, 2012,
Wei Fan, Albert Bifet, Qiang Yang, Philip Yu,
BigMine 2012
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