2023
Heitor Murilo Gomes, Maciej Grzenda, Rodrigo Fernandes de Mello, Jesse Read, Minh-Huong Le Nguyen, Albert Bifet:
A Survey on Semi-supervised Learning for Delayed Partially Labelled Data Streams. ACM Comput. Surv. 55(4): 75:1-75:42 (2023)
Jesus Antonanzas, Yunzhe Jia, Eibe Frank, Albert Bifet, Bernhard Pfahringer:
teex: A toolbox for the evaluation of explanations. Neurocomputing 555: 126642 (2023)
Akshaya Ravi, Mounira Msahli, Han Qiu, Gérard Memmi, Albert Bifet, Meikang Qiu:
Wangiri Fraud: Pattern Analysis and Machine-Learning-Based Detection. IEEE Internet Things J. 10(8, April 15): 6794-6802 (2023)
Vítor Cerqueira, Heitor Murilo Gomes, Albert Bifet, Luís Torgo:
STUDD: a student-teacher method for unsupervised concept drift detection. Mach. Learn. 112(11): 4351-4378 (2023)
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
Combining Diverse Meta-Features to Accurately Identify Recurring Concept Drift in Data Streams. ACM Trans. Knowl. Discov. Data 17(8): 107:1-107:36 (2023)
Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing. IEEE Trans. Netw. Serv. Manag. 20(3): 3038-3054 (2023)
Anton Lee, Yaqian Zhang, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning. CIKM 2023: 4038-4042
Zichong Wang, Nripsuta Saxena, Tongjia Yu, Sneha Karki, Tyler Zetty, Israat Haque, Shan Zhou, Dukka Kc, Ian Stockwell, Xuyu Wang, Albert Bifet, Wenbin Zhang:
Preventing Discriminatory Decision-making in Evolving Data Streams. FAccT 2023: 149-159
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:
StreamMLOps: Operationalizing Online Learning for Big Data Streaming & Real-Time Applications. ICDE 2023: 3508-3521
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
FALL: A Modular Adaptive Learning Platform for Streaming Data. ICDE 2023: 3619-3622
Mariam Barry, Albert Bifet, Jean-Luc Billy:
StreamAI: Dealing with Challenges of Continual Learning Systems for Serving AI in Production. ICSE-SEIP 2023: 134-137
Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
Survey on Online Streaming Continual Learning. IJCAI 2023: 6628-6637
Zichong Wang, Charles Wallace, Albert Bifet, Xin Yao, Wenbin Zhang:
FG2AN: Fairness-Aware Graph Generative Adversarial Networks. ECML/PKDD (2) 2023: 259-275
João Vinagre, Marie Al-Ghossein, Ladislav Peska, Alípio Mário Jorge, Albert Bifet:
ORSUM 2023 – 6th Workshop on Online Recommender Systems and User Modeling. RecSys 2023: 1272-1273
Martha Roseberry, Saso Dzeroski, Albert Bifet, Alberto Cano:
Aging and rejuvenating strategies for fading windows in multi-label classification on data streams. SAC 2023: 390-397
2022
Md. Mahbub Alam, Luís Torgo, Albert Bifet:
A Survey on Spatio-temporal Data Analytics Systems. ACM Comput. Surv. 54(10s): 219:1-219:38 (2022)
Chaitanya Manapragada, Heitor Murilo Gomes, Mahsa Salehi, Albert Bifet, Geoffrey I. Webb:
An eager splitting strategy for online decision trees in ensembles. Data Min. Knowl. Discov. 36(2): 566-619 (2022)
Yibin Sun, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams. Data Min. Knowl. Discov. 36(5): 2006-2032 (2022)
Natalia Mordvanyuk, Albert Bifet, Beatriz López:
VEPRECO: Vertical databases with pre-pruning strategies and common candidate selection policies to fasten sequential pattern mining. Expert Syst. Appl. 204: 117517 (2022)
Ioan Petri, Ioan Chirila, Heitor Murilo Gomes, Albert Bifet, Omer F. Rana:
Resource-Aware Edge-Based Stream Analytics. IEEE Internet Comput. 26(4): 79-88 (2022)
Emanuele Pio Barracchia, Gianvito Pio, Albert Bifet, Heitor Murilo Gomes, Bernhard Pfahringer, Michelangelo Ceci:
LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding. Inf. Sci. 606: 702-721 (2022)
Natalia Mordvanyuk, Beatriz López, Albert Bifet:
TA4L: Efficient temporal abstraction of multivariate time series. Knowl. Based Syst. 244: 108554 (2022)
Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson:
Analyzing and repairing concept drift adaptation in data stream classification. Mach. Learn. 111(10): 3489-3523 (2022)
Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, João Gama, Georges Hébrail, Vincent Lemaire, Pierre-Francois Marteau:
Open challenges for Machine Learning based Early Decision-Making research. SIGKDD Explor. 24(2): 12-31 (2022)
João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet, Paolo Cremonesi:
Preface to the special issue on dynamic recommender systems and user models. User Model. User Adapt. Interact. 32(4): 503-507 (2022)
Minh-Huong Le Nguyen, Fabien Turgis, Pierre-Emmanuel Fayemi, Albert Bifet:
Continuous Health Monitoring of Machinery using Online Clustering on Unlabeled Data Streams. IEEE Big Data 2022: 1866-1873
Mariam Barry, Albert Bifet, Raja Chiky, Saad El Jaouhari, Jacob Montiel, Aissa El Ouafi, Eric Guerizec:
Stream2Graph: Dynamic Knowledge Graph for Online Learning Applied in Large-scale Network. IEEE Big Data 2022: 2190-2197
Mariam Barry, Saad El Jaouhari, Albert Bifet, Jacob Montiel, Eric Guerizec, Raja Chiky:
StreamFlow: A System for Summarizing and Learning Over Industrial Big Data Streams. IEEE Big Data 2022: 2198-2205
Nuwan Gunasekara, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Adaptive Neural Networks for Online Domain Incremental Continual Learning. DS 2022: 89-103
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams. DSAA 2022: 1-10
Nuwan Gunasekara, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Adaptive Online Domain Incremental Continual Learning. ICANN (1) 2022: 491-502
Thomas Guyet, Wenbin Zhang, Albert Bifet:
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrences. ICCS (1) 2022: 460-472
Dihia Boulegane, Vitor Cerquiera, Albert Bifet:
Adaptive Model Compression of Ensembles for Evolving Data Streams Forecasting. IJCNN 2022: 1-8
Nuwan Gunasekara, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet:
Online Hyperparameter Optimization for Streaming Neural Networks. IJCNN 2022: 1-9
Jacob Montiel, Hoang-Anh Ngo, Minh-Huong Le Nguyen, Albert Bifet:
Online Clustering: Algorithms, Evaluation, Metrics, Applications and Benchmarking. KDD 2022: 4808-4809
Peng Yu, Albert Bifet, Jesse Read, Chao Xu:
Linear tree shap. NeurIPS 2022
Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia:
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal. NeurIPS 2022
Cedric Kulbach, Jacob Montiel, Maroua Bahri, Marco Heyden, Albert Bifet:
Evolution-Based Online Automated Machine Learning. PAKDD (1) 2022: 472-484
João Vinagre, Marie Al-Ghossein, Alípio Mário Jorge, Albert Bifet, Ladislav Peska:
ORSUM 2022 – 5th Workshop on Online Recommender Systems and User Modeling. RecSys 2022: 661-662
Zijing Zhang, Vimal Kumar, Michael Mayo, Albert Bifet:
Assessing Vulnerability from Its Description. UbiSec 2022: 129-143
2021
Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet:
Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency. Data Min. Knowl. Discov. 35(3): 796-836 (2021)
Jesus L. Lobo, Javier Del Ser, Eneko Osaba, Albert Bifet, Francisco Herrera:
CURIE: a cellular automaton for concept drift detection. Data Min. Knowl. Discov. 35(6): 2655-2678 (2021)
José del Campo-Ávila, Abdelatif Takilalte, Albert Bifet, Llanos Mora López:
Binding data mining and expert knowledge for one-day-ahead prediction of hourly global solar radiation. Expert Syst. Appl. 167: 114147 (2021)
Natalia Mordvanyuk, Beatriz López, Albert Bifet:
vertTIRP: Robust and efficient vertical frequent time interval-related pattern mining. Expert Syst. Appl. 168: 114276 (2021)
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs. Fundam. Informaticae 182(3): 219-242 (2021)
Eva García-Martín, Albert Bifet, Niklas Lavesson:
Energy modeling of Hoeffding tree ensembles. Intell. Data Anal. 25(1): 81-104 (2021)
Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Improving the performance of bagging ensembles for data streams through mini-batching. Inf. Sci. 580: 260-282 (2021)
Jacob Montiel, Max Halford, Saulo Martiello Mastelini, Geoffrey Bolmier, Raphaël Sourty, Robin Vaysse, Adil Zouitine, Heitor Murilo Gomes, Jesse Read, Talel Abdessalem, Albert Bifet:
River: machine learning for streaming data in Python. J. Mach. Learn. Res. 22: 110:1-110:8 (2021)
Heitor Murilo Gomes, Jesse Read, Albert Bifet, Robert J. Durrant:
Learning from evolving data streams through ensembles of random patches. Knowl. Inf. Syst. 63(7): 1597-1625 (2021)
Maroua Bahri, Albert Bifet, João Gama, Heitor Murilo Gomes, Silviu Maniu:
Data stream analysis: Foundations, major tasks and tools. WIREs Data Mining Knowl. Discov. 11(3) (2021)
Mariam Barry, Albert Bifet, Raja Chiky, Jacob Montiel, Vinh-Thuy Tran:
Challenges of Machine Learning for Data Streams in the Banking Industry. BDA 2021: 106-118
Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Kalman Filtering for Learning with Evolving Data Streams. IEEE BigData 2021: 5337-5346
Nicolas Kourtellis, Herodotos Herodotou, Maciej Grzenda, Piotr Wawrzyniak, Albert Bifet:
S2CE: a hybrid cloud and edge orchestrator for mining exascale distributed streams. DEBS 2021: 103-113
Maroua Bahri, Albert Bifet:
Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams. DS 2021: 122-137
Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson:
Analyzing and Repairing Concept Drift Adaptation in Data Stream Classification. DSAA 2021: 1-2
Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet, Russel Pears:
Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information. ICDE 2021: 1056-1067
Nedeljko Radulovic, Albert Bifet, Fabian M. Suchanek:
Confident Interpretations of Black Box Classifiers. IJCNN 2021: 1-8
Saulo Martiello Mastelini, Jacob Montiel, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, André C. P. L. F. de Carvalho:
Fast and lightweight binary and multi-branch Hoeffding Tree Regressors. ICDM (Workshops) 2021: 380-388
Wenbin Zhang, Albert Bifet, Xiangliang Zhang, Jeremy C. Weiss, Wolfgang Nejdl:
FARF: A Fair and Adaptive Random Forests Classifier. PAKDD (2) 2021: 245-256
Yunzhe Jia, Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Lim:
Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality. ECML/PKDD (2) 2021: 699-714
Einav Peretz-Andersson, Niklas Lavesson, Albert Bifet, Patrick Mikalef:
AI Transformation in the Public Sector: Ongoing Research. SAIS 2021: 1-4
2020
Albert Bifet, João Gama:
IoT data stream analytics. Ann. des Télécommunications 75(9-10): 491-492 (2020)
Maciej Grzenda, Heitor Murilo Gomes, Albert Bifet:
Delayed labelling evaluation for data streams. Data Min. Knowl. Discov. 34(5): 1237-1266 (2020)
Paulo Cortez, Albert Bifet:
Fifth special issue on knowledge discovery and business intelligence. Expert Syst. J. Knowl. Eng. 37(6) (2020)
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet, Meriem Bouzbila:
Sampling informative patterns from large single networks. Future Gener. Comput. Syst. 106: 653-658 (2020)
Nedeljko Radulovic, Dihia Boulegane, Albert Bifet:
SCALAR – A Platform for Real-time Machine Learning Competitions on Data Streams. J. Open Source Softw. 5(55): 2676 (2020)
Yiyan Qi, Jiefeng Cheng, Xiaojun Chen, Reynold Cheng, Albert Bifet, Pinghui Wang:
Discriminative Streaming Network Embedding. Knowl. Based Syst. 190: 105138 (2020)
Jesus L. Lobo, Javier Del Ser, Albert Bifet, Nikola K. Kasabov:
Spiking Neural Networks and online learning: An overview and perspectives. Neural Networks 121: 88-100 (2020)
Jesus L. Lobo, Izaskun Oregi, Albert Bifet, Javier Del Ser:
Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning. Neural Networks 123: 118-133 (2020)
Alessio Bernardo, Heitor Murilo Gomes, Jacob Montiel, Bernhard Pfahringer, Albert Bifet, Emanuele Della Valle:
C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams. IEEE BigData 2020: 483-492
Maroua Bahri, Bruno Veloso, Albert Bifet, João Gama:
AutoML for Stream k-Nearest Neighbors Classification. IEEE BigData 2020: 597-602
Dihia Boulegane, Albert Bifet, Haytham Elghazel, Giyyarpuram Madhusudan:
Streaming Time Series Forecasting using Multi-Target Regression with Dynamic Ensemble Selection. IEEE BigData 2020: 2170-2179
Wenbin Zhang, Albert Bifet:
FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier. DS 2020: 175-189
Vítor Cerqueira, Heitor Murilo Gomes, Albert Bifet:
Unsupervised Concept Drift Detection Using a Student-Teacher Approach. DS 2020: 190-204
Maroua Bahri, Albert Bifet, Silviu Maniu, Rodrigo Fernandes de Mello, Nikolaos Tziortziotis:
Compressed k-Nearest Neighbors Ensembles for Evolving Data Streams. ECAI 2020: 961-968
Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Improving parallel performance of ensemble learners for streaming data through data locality with mini-batching. HPCC/DSS/SmartCity 2020: 138-146
Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Incremental Rebalancing Learning on Evolving Data Streams. ICDM (Workshops) 2020: 844-850
Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Fast Incremental Naïve Bayes with Kalman Filtering. ICDM (Workshops) 2020: 883-889
Maroua Bahri, Bernhard Pfahringer, Albert Bifet, Silviu Maniu:
Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams. IDA 2020: 40-53
Maroua Bahri, Albert Bifet, Silviu Maniu, Heitor Murilo Gomes:
Survey on Feature Transformation Techniques for Data Streams. IJCAI 2020: 4796-4802
Maroua Bahri, Heitor Murilo Gomes, Albert Bifet, Silviu Maniu:
CS-ARF: Compressed Adaptive Random Forests for Evolving Data Stream Classification. IJCNN 2020: 1-8
Heitor Murilo Gomes, Jacob Montiel, Saulo Martiello Mastelini, Bernhard Pfahringer, Albert Bifet:
On Ensemble Techniques for Data Stream Regression. IJCNN 2020: 1-8
Maciej Grzenda, Heitor Murilo Gomes, Albert Bifet:
Performance measures for evolving predictions under delayed labelling classification. IJCNN 2020: 1-8
Viktor Losing, Barbara Hammer, Heiko Wersing, Albert Bifet:
Randomizing the Self-Adjusting Memory for Enhanced Handling of Concept Drift. IJCNN 2020: 1-8
Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet:
Adaptive XGBoost for Evolving Data Streams. IJCNN 2020: 1-8
Matthias Carnein, Heike Trautmann, Albert Bifet, Bernhard Pfahringer:
confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms. LION 2020: 80-95
Minh-Huong Le Nguyen, Fabien Turgis, Pierre-Emmanuel Fayemi, Albert Bifet:
Challenges of Stream Learning for Predictive Maintenance in the Railway Sector. IoT Streams/ITEM@PKDD/ECML 2020: 14-29
2019
Jean Paul Barddal, Fabrício Enembreck, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer: Merit-guided dynamic feature selection filter for data streams. Expert Syst. Appl. 116: 227-242 (2019)
Rodrigo Fernandes de Mello, Yule Vaz, Carlos Henrique Grossi Ferreira, Albert Bifet: On learning guarantees to unsupervised concept drift detection on data streams. Expert Syst. Appl. 117: 90-102 (2019)
Rodrigo Fernandes de Mello, Chaitanya Manapragada, Albert Bifet: Measuring the Shattering coefficient of Decision Tree models. Expert Syst. Appl. 137: 443-452 (2019)
Robert Anderson, Yun Sing Koh, Gillian Dobbie, Albert Bifet: Recurring concept meta-learning for evolving data streams. Expert Syst. Appl. 138 (2019)
Abhik Ray, Lawrence B. Holder, Albert Bifet: Efficient frequent subgraph mining on large streaming graphs. Intell. Data Anal. 23(1): 103-132 (2019)
Jesse Read, Albert Bifet, Wei Fan, Qiang Yang, Philip S. Yu: Introduction to the special issue on Big Data, IoT Streams and Heterogeneous Source Mining. Int. J. Data Sci. Anal. 8(3): 221-222 (2019)
Jean Paul Barddal, Fabrício Enembreck, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer: Boosting decision stumps for dynamic feature selection on data streams. Inf. Syst. 83: 13-29 (2019)
Heitor Murilo Gomes, Jesse Read, Albert Bifet, Jean Paul Barddal, João Gama: Machine learning for streaming data: state of the art, challenges, and opportunities. SIGKDD Explorations 21(2): 6-22 (2019)
Minh-Huong Le Nguyen, Heitor Murilo Gomes, Albert Bifet: Semi-supervised Learning over Streaming Data using MOA. BigData 2019: 553-562
Heitor Murilo Gomes, Rodrigo Fernandes de Mello, Bernhard Pfahringer, Albert Bifet: Feature Scoring using Tree-Based Ensembles for Evolving Data Streams. BigData 2019: 761-769
Dihia Boulegane, Albert Bifet, Giyyarpuram Madhusudan: Arbitrated Dynamic Ensemble with Abstaining for Time-Series Forecasting on Data Streams. BigData 2019: 1040-1045
Dihia Boulegane, Nedeljko Radulovic, Albert Bifet, Ghislain Fiévet, Jimin Sohn, Yeonwoo Nam, Seojeong Yu, Dong-Wan Choi: Real-Time Machine Learning Competition on Data Streams at the IEEE Big Data 2019. BigData 2019: 3493-3497
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem: Adaptive Algorithms for Estimating Betweenness and k-path Centralities. CIKM 2019: 1231-1240
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet: Metropolis-Hastings Algorithms for Estimating Betweenness Centrality. EDBT 2019: 686-689
Heitor Murilo Gomes, Jesse Read, Albert Bifet: Streaming Random Patches for Evolving Data Stream Classification. ICDM 2019: 240-249
Heitor Murilo Gomes, Albert Bifet, Philippe Fournier-Viger, Jones Granatyr, Jesse Read: Network of Experts: Learning from Evolving Data Streams Through Network-Based Ensembles. ICONIP (1) 2019: 704-716
Luis Eduardo Boiko Ferreira, Heitor Murilo Gomes, Albert Bifet, Luiz S. Oliveira: Adaptive Random Forests with Resampling for Imbalanced data Streams. IJCNN 2019: 1-6
Guilherme Weigert Cassales, Hermes Senger, Elaine Ribeiro de Faria, Albert Bifet: IDSA-IoT: An Intrusion Detection System Architecture for IoT Networks. ISCC 2019: 1-7
Riccardo Tommasini, Robin Keskisärkkä, Jean-Paul Calbimonte, Eva Blomqvist, Emanuele Della Valle, Albert Bifet: Continuous Analytics of Web Streams. WWW (Companion Volume) 2019: 1323-1325
2018
Albert Bifet, Ricard Gavalda, Geoff Holmes, Bernhard Pfahringer: Machine Learning for Data Streams with Practical Examples in MOA. MIT Press, 2018.
Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem: Scikit-Multiflow: A Multi-output Streaming Framework. J. Mach. Learn. Res. 19: 72:1-72:5 (2018)
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem: Discriminative Distance-Based Network Indices with Application to Link Prediction. Comput. J. 61(7): 998-1014 (2018)
Pinghui Wang, Feiyang Sun, Di Wang, Jing Tao, Xiaohong Guan, Albert Bifet: Predicting attributes and friends of mobile users from AP-Trajectories. Inf. Sci. 463-464: 110-128 (2018)
Albert Bifet, Jesse Read: Ubiquitous Artificial Intelligence and Dynamic Data Streams. DEBS 2018: 1-6
Andrian Putina, Steven Barth, Albert Bifet, Drew Pletcher, Cristina Precup, Patrice Nivaggioli, Dario Rossi: Unsupervised real-time detection of BGP anomalies leveraging high-rate and fine-grained telemetry data. INFOCOM Workshops 2018: 1-2
Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem: Scalable Model-Based Cascaded Imputation of Missing Data. PAKDD (3) 2018: 64-76
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem: Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs. PAKDD (3) 2018: 752-764
Andrian Putina, Dario Rossi, Albert Bifet, Steven Barth, Drew Pletcher, Cristina Precup, Patrice Nivaggioli: Telemetry-based stream-learning of BGP anomalies. Big-DAMA@SIGCOMM 2018: 15-20
Maroua Bahri, Silviu Maniu, Albert Bifet: A Sketch-Based Naive Bayes Algorithms for Evolving Data Streams. BigData 2018: 604-613
Jacob Montiel, Albert Bifet, Viktor Losing, Jesse Read, Talel Abdessalem: Learning Fast and Slow: A Unified Batch/Stream Framework. BigData 2018: 1065-1072
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem: An In-depth Comparison of Group Betweenness Centrality Estimation Algorithms. BigData 2018: 2104-2113
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem: DyBED: An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs. BigData 2018: 2114-2123
Heitor Murilo Gomes, Jean Paul Barddal, Luis Eduardo Boiko Ferreira, Albert Bifet: Adaptive random forests for data stream regression. ESANN 2018
Tian Guo, Albert Bifet, Nino Antulov-Fantulin: Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders. ICDM 2018: 989-994
Fei Song, Yanlei Diao, Jesse Read, Arnaud Stiegler, Albert Bifet: EXAD: A System for Explainable Anomaly Detection on Big Data Traces. ICDM Workshops 2018: 1435-1440
2017
Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfharinger, Geoff Holmes, Talel Abdessalem: Adaptive random forests for evolving data stream classification. Machine Learning, Springer, 2017.
Heitor Murilo Gomes, Jean Paul Barddal, Fabrício Enembreck, and Albert Bifet: A Survey on Ensemble Learning for Data Stream Classification. ACM Comput. Surv. 50, 2, Article 23 (March 2017).
Diego Marron, Eduard Ayguadé, José R. Herrero, Jesse Read, Albert Bifet: Low-latency multi-threaded ensemble learning for dynamic big data streams. BigData 2017: 223-232
Jacob Montiel, Albert Bifet, Talel Abdessalem: Predicting over-indebtedness on batch and streaming data. BigData 2017: 1504-1513
Diego Marron, Jesse Read, Albert Bifet, Nacho Navarro: Data stream classification using random feature functions and novel method combinations. Journal of Systems and Software 127: 195-204 (2017)
Albert Bifet: Classifier Concept Drift Detection and the Illusion of Progress. ICAISC (2) 2017: 715-725
Pierre-Xavier Loeffel, Albert Bifet, Christophe Marsala, Marcin Detyniecki: Droplet Ensemble Learning on Drifting Data Streams. IDA 2017: 210-222
Albert Bifet, Jiajin Zhang, Wei Fan, Cheng He, Jianfeng Zhang, Jianfeng Qian, Geoff Holmes, Bernhard Pfahringer: Extremely Fast Decision Tree Mining for Evolving Data Streams. KDD 2017: 1733-1742
Pinghui Wang, Feiyang Sun, Di Wang, Jing Tao, Xiaohong Guan, Albert Bifet: Inferring Demographics and Social Networks of Mobile Device Users on Campus From AP-Trajectories. WWW (Companion Volume) 2017: 139-147
2016
João Duarte, João Gama, Albert Bifet: Adaptive Model Rules From High-Speed Data Streams. TKDD 10(3): 30 (2016)
Valentín Carela-Español, Pere Barlet-Ros, Albert Bifet, Kensuke Fukuda: A streaming flow-based technique for traffic classification applied to 12 + 1 years of Internet traffic. Telecommunication Systems 63(2): 191-204 (2016)
Gianmarco De Francisci Morales, Albert Bifet, Latifur Khan, João Gama, Wei Fan: IoT Big Data Stream Mining. KDD 2016: 2119-2120
Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet, Arinto Murdopo: VHT: Vertical Hoeffding Tree. IEEE BigData (2016)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck, Bernhard Pfahringer, Albert Bifet: On Dynamic Feature Weighting for Feature Drifting Data Streams. ECML/PKDD (2) 2016: 129-144
Diego Marron, Jesse Read, Albert Bifet, Talel Abdessalem, Eduard Ayguadé, José R. Herrero. Echo State Hoeffding Tree Learning. ACML 2016: The 8th Asian Conference on Machine Learning 2016.
Michael Mayo, Albert Bifet: Deferral classification of evolving temporal dependent data streams. SAC 2016: 952-954
2015
Albert Bifet, Gianmarco De Francisci Morales, Jesse Read, Bernhard Pfahringer and Geoff Holmes: Efficient Online Evaluation of Big Data Stream Classifiers, KDD 2015.
Gianmarco De Francisci Morales and Albert Bifet: SAMOA: Scalable Advanced Massive Online Analysis, Journal of Machine Learning Research, 16(Jan):149–153, 2015.
Sripirakas Sakthithasan, Russel Pears, Albert Bifet, Bernhard Pfahringer: Use of ensembles of Fourier spectra in capturing recurrent concepts in data streams. IJCNN 2015: 1-8
Albert Bifet: Mining Big Data Streams with Apache SAMOA. MUSE@PKDD/ECML 2015: 55
David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet:
Drift Detection Using Stream Volatility. ECML/PKDD (1) 2015: 417-432
Albert Bifet: Real-Time Big Data Stream Analytics. SIMBig 2015: 13-14
Jesse Read, Albert Bifet: Data Stream Classification Using Random Feature Functions and Novel Method Combinations. TrustCom/BigDataSE/ISPA (2) 2015: 211-216
Jesse Read, Fernando Perez-Cruz and Albert Bifet. Deep Learning in Partially-labeled Data Streams. SAC 2015.
Indrė Žliobaitė, Albert Bifet, Jesse Read, Bernhard Pfahringer and Geoff Holmes:
Evaluation methods and decision theory for classification of streaming data with temporal dependence.
Machine Learning 98(3): 455-482 (2015)
Massimo Quadrana, Albert Bifet, Ricard Gavaldà: An efficient closed frequent itemset miner for the MOA stream mining system. AI Commun. 28(1): 143-158 (2015)
2014
Jesse Read, Antti Puurula, Albert Bifet: Multi-label Classification with Meta Labels. International Conference on Data Mining (ICDM 2014). December 2014.
Albert Bifet and Gianmarco De Francisci Morales: Big Data Stream Learning with SAMOA. Data Mining Workshop (ICDMW), 2014 IEEE International Conference on, 1199-1202. December 2014.
Brandon S Parker, Latifur Khan, Albert Bifet: Incremental Ensemble Classifier Addressing Non-stationary Fast Data Streams. Data Mining Workshop (ICDMW), 2014 IEEE International Conference on, 716-723. December 2014.
Antti Puurula, Jesse Read and Albert Bifet: Kaggle LSHTC4 Winning Solution. arXiv:1405.0546
Anh Thu Vu, Gianmarco De Francisci Morales, Joao Gama, and Albert Bifet: Distributed Adaptive Model Rules for Mining Big Data Streams. IEEE International Conference on Big Data 2014.
Diego Marron, Albert Bifet, Gianmarco De Francisci Morales: Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams. ECAI 2014: 615-620
Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet: Change detection in categorical evolving data streams. SAC 2014: 792-797
Indrė Žliobaitė, Albert Bifet, Bernhard Pfahringer and Geoff Holmes: Active Learning with Drifting Streaming Data. IEEE Transactions on Neural Networks and Learning Systems 25(1): 27-39 (2014)
Joao Gama, Indrė Žliobaitė, Albert Bifet, Mykola Pechenizkiy, and Abdelhamid Bouchachia: A Survey on Concept Drift Adaptation. ACM Computing Surveys, 46(4), 2014.
Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet: Détection de changements dans des flots de données qualitatives. EGC 2014: 517-520
2013
Albert Bifet: Mining Big Data in Real Time, Informatica Journal, Volume 37, Number 1, 2013
Konstantin Kutzkov, Albert Bifet, Francesco Bonchi, Aris Gionis STRIP: Stream Learning of Influence Probabilities KDD 2013.
Albert Bifet, Indrė Žliobaitė, Jesse Read, Bernhard Pfahringer and Geoff Holmes: Pitfalls in benchmarking data stream classification and how to avoid them ECML-PKDD 2013
Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes, and Indrė Žliobaitė: CD-MOA: Change Detection Framework for Massive Online Analysis. Proc. of the 20th Int. Symposium on Intelligent Data Analysis, IDA’13.
Dino Ienco, Albert Bifet, Indrė Žliobaitė and Bernhard Pfahringer: Clustering Based Active Learning for Evolving Data Stream DS 2013
Albert Bifet, Bernhard Pfahringer, Jesse Read, Geoff Holmes: Efficient data stream classification via probabilistic adaptive windows. SAC 2013: 801-806
Massimo Quadrana, Albert Bifet and Ricard Gavaldà: An Efficient Closed Frequent Itemset Miner for the MOA Stream Mining System IOS Press Frontiers in Artificial Intelligence and Applications, vol. 256, 157-166. Slides by Ricard Gavaldà.
2012
Wei Fan, Albert Bifet: Mining Big Data: Current Status, and Forecast to the Future. SIGKDD Explorations 14(2): 1-5 (2012) [pdf]
Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer: Scalable and efficient multi-label classification for evolving data streams. Machine Learning 88(1-2): 243-272 (2012).
Indrė Žliobaitė, Albert Bifet, Mohamed Medhat Gaber, Bogdan Gabrys, Joao Gama, Leandro L. Minku, Katarzyna Musial: Next challenges for adaptive learning systems. SIGKDD Explorations 14(1): 48-55 (2012) [pdf]
Albert Bifet, Eibe Frank, Geoff Holmes, Bernhard Pfahringer: Ensembles of Restricted Hoeffding Trees. ACM TIST 3(2): 30 (2012) [pdf]
Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read: Stream Data Mining Using the MOA Framework. DASFAA (2) 2012: 309-313
Jesse Read, Albert Bifet, Bernhard Pfahringer, Geoff Holmes: Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data. IDA 2012: 313-323
Anti Puurula and Albert Bifet. Ensembles of Sparse Multinomial Classifiers for Scalable Text Classification. In ECML/PKDD PASCAL Workshop on Large-Scale Hierarchical Classification, 2012.
2011
Albert Bifet, Geoff Holmes, Bernhard Pfahringer and Ricard Gavaldà: Mining Frequent Closed Graphs on Evolving Data Streams. 17th ACM SIGKDD Intl. Conference on Knowledge Discovery and Data Mining KDD’11.
Hardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes and Bernhard Pfahringer: An Effective Evaluation Measure for Clustering on Evolving Data Stream. 17th ACM SIGKDD Intl. Conference on Knowledge Discovery and Data Mining KDD’11.
Indrė Žliobaitė, Albert Bifet, Bernhard Pfahringer and Geoff Holmes: Active learning with evolving streaming data. Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2011.
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, and Thomas Seidl. MOA: a Real-time Analytics Open Source Framework. Demo at Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2011
Albert Bifet, Ricard Gavaldà: Mining frequent closed trees in evolving data streams. Intell. Data Anal. 15(1): 29-48 (2011)
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Ricard Gavaldà: Detecting Sentiment Change in Twitter Streaming Data. Journal of Machine Learning Research – Proceedings Track 17: 5-11 (2011) [pdf]
José M. Carmona-Cejudo, Manuel Baena-García, Rafael Morales Bueno, João Gama, Albert Bifet: Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classification. Journal of Machine Learning Research – Proceedings Track 17: 12-18 (2011) [pdf]
Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer: Streaming Multi-label Classification. Journal of Machine Learning Research – Proceedings Track 17: 19-25 (2011) [pdf]
Indre Zliobaite, Albert Bifet, Geoff Holmes, Bernhard Pfahringer: MOA Concept Drift Active Learning Strategies for Streaming Data. Journal of Machine Learning Research – Proceedings Track 17: 48-55 (2011) [pdf]
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer: MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data. Discovery Science 2011: 46-60
José M. Carmona-Cejudo, Manuel Baena-García, José del Campo-Ávila, Albert Bifet, João Gama, Rafael Morales Bueno: Online Evaluation of Email Streaming Classifiers Using GNUsmail. IDA 2011: 90-100
2010
Albert Bifet, Geoff Holmes, and Bernhard Pfahringer. Leveraging Bagging for Evolving Data Streams.[pdf] | ECML PKDD 2010, Barcelona, Catalonia, 2010.
Albert Bifet, Eibe Frank, Geoff Holmes, and Bernhard Pfahringer. “Accurate ensembles for data streams: Combining restricted Hoeffding trees using stacking.” [pdf] Proc 2nd Asian Conference on Machine Learning, Tokyo. JMLR, 2010.
Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer: Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA. ICDM Workshops 2010: 1400-1403
José M. Carmona-Cejudo, Manuel Baena-García, José del Campo-Ávila, Rafael Morales Bueno, Albert Bifet: GNUsmail: Open Framework for On-line Email Classification. ECAI 2010: 1141-1142
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl. “MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering”. [pdf]Workshop on Applications of Pattern Analysis, JMLR, 2010.
Albert Bifet and Eibe Frank. “Sentiment knowledge discovery in Twitter streaming data”. [pdf] Proc 13th International Conference on Discovery Science, Canberra, Australia.
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl. “MOA: Massive online analysis, a framework for stream classification and clustering.” [pdf]Pechenizkiy, M. and Žliobaitė, I. (eds), HaCDAIS Workshop ECML-PKDD 2010, 2010.
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, and Eibe Frank. “Fast Perceptron Decision Tree Learning from Evolving Data Streams” [pdf] Advances in Knowledge Discovery and Data Mining, 14th Pacific-Asia Conference, PAKDD 2010.
Albert Bifet, Geoff Holmes, Richard Kirkby, and Bernhard Pfahringer. “MOA: Massive online analysis.”Journal of Machine Learning Research (JMLR), 2010.
José Luis Balcázar, Albert Bifet and Antoni Lozano: ” Mining Frequent Closed Rooted Trees “. [pdf] | Machine Learning Journal (78:1), 2010, 1-33.
2009
Albert Bifet Thesis: Adaptive Learning and Mining for Data Streams and Frequent Patterns Advised byRicard Gavaldà and José Luis Balcázar.
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Richard Kirkby, and Ricard Gavaldà: ” New ensemble methods for evolving data streams” . In 15th ACM SIGKDD Intl. Conference on Knowledge Discovery and Data Mining (KDD’09), Paris, France, June 2009.
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, and Ricard Gavaldà: “Improving Adaptive Bagging Methods for Evolving Data Streams” . In First Asian Conference on Machine Learning, ACML 2009, Nanjing, China, November 2009.
Albert Bifet and Ricard Gavaldà: “ Adaptive XML Tree Classification on Evolving Data Streams“. [pdf] | ECML PKDD 2009
Albert Bifet and Ricard Gavaldà: “ Adaptive Learning from Evolving Data Streams“. | IDA 2009 | Extended Version Technical Report LSI R09-9
Albert Bifet: Adaptive learning and mining for data streams and frequent patterns. SIGKDD Explorations 11(1): 55-56 (2009)
2008
Albert Bifet and Ricard Gavaldà: “ Mining adaptively frequent closed unlabeled rooted trees in data streams“. [pdf] | [Software] | [Datasets] | [Slides] . In 14th ACM SIGKDD Intl. Conference on Knowledge Discovery and Data Mining (KDD’08), Las Vegas, USA, August 2008.
José Luis Balcázar, Albert Bifet and Antoni Lozano: “ Mining Implications from Lattices of Closed Trees “.[pdf]| [slides] | Extraction et Gestion des Connaissances EGC’2008, Sophia Antipolis, France.
2007
José Luis Balcázar, Albert Bifet and Antoni Lozano: “ Closed and maximal tree mining using natural representations“. [pdf] | Workshop on Mining and Learning with Graphs MLG 2007.
José Luis Balcázar, Albert Bifet and Antoni Lozano: “ Subtree Testing and Closed Tree Mining Through Natural Representations “. [pdf] | ACKE Workshop on “Advances in Conceptual Knowledge Engineering” 2007, Regensburg, Germany.
José Luis Balcázar, Albert Bifet and Antoni Lozano: “ Mining Frequent Closed Unordered Trees Through Natural Representations “. [pdf] | [slides] | In 2007 International Conference on Conceptual Structures, Sheffield UK.
Albert Bifet and Ricard Gavaldà: “ Learning from Time-Changing Data with Adaptive Windowing“. [pdf] |[pdf extended version] . Poster. In 2007 SIAM International Conference on Data Mining (SDM’07), Minneapolis, Minnesota.
2006
Albert Bifet and Ricard Gavaldà: “ Kalman Filters and Adaptive Windows for Learning in Data Streams “.[pdf] | [pdf extended version]| [slides] | Proc. 9th International Conference on Discovery Sicence (DS 2006). Springer-Verlag Lecture Notes in Artificial Intelligence 4265, 29-40.
José Luis Balcázar, Albert Bifet and Antoni Lozano: “ Intersection Algorithms and a Closure Operator on Unordered Trees “. [pdf] | Workshop Mining and Learning with Graphs MLG 2006.
Manuel Baena-García, José del Campo-Ávila, Raúl Fidalgo, Albert Bifet , Ricard Gavaldà and Rafael Morales-Bueno: “ Early Drift Detection Method “. [pdf] | ECML PKDD Workshop on Knowledge Discovery from Data Streams 2006.
2005
Albert Bifet, Carlos Castillo, Paul-Alexandru Chirita and Ingmar Weber: “ An Analysis of Factors Used in Search Engine Ranking“.| [pdf] | [slides] Workshop on Adversarial Information Retrieval on the Web (synopsis), 2005.