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ORCIDAlbert Bifet
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- affiliation: University of Waikato, Hamilton, New Zealand
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2020 – today
- 2025
[j73]Guilherme Weigert Cassales, Serajis Salekin, Nick Jin Sean Lim, Dean F. Meason
, Albert Bifet, Bernhard Pfahringer, Eibe Frank:
A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study. Ecol. Informatics 86: 103014 (2025)- [j72]Zijing Zhang, Vimal Kumar, Bernhard Pfahringer, Albert Bifet:
Ai-enabled automated common vulnerability scoring from common vulnerabilities and exposures descriptions. Int. J. Inf. Sec. 24(1): 16 (2025) - [c161]Nilesh Verma, Albert Bifet, Bernhard Pfahringer, Maroua Bahri:
ASML-REG: Automated Machine Learning for Data Stream Regression. SAC 2025: 440-447 - [i47]Yibin Sun, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet:
Evaluation for Regression Analyses on Evolving Data Streams. CoRR abs/2502.07213 (2025) - [i46]Heitor Murilo Gomes, Anton Lee, Nuwan Gunasekara, Yibin Sun, Guilherme Weigert Cassales, Justin Liu, Marco Heyden, Vítor Cerqueira, Maroua Bahri, Yun Sing Koh, Bernhard Pfahringer, Albert Bifet:
CapyMOA: Efficient Machine Learning for Data Streams in Python. CoRR abs/2502.07432 (2025) - 2024
- [j71]Abdul Wahid, Mounira Msahli, Albert Bifet, Gérard Memmi:
NFA: A neural factorization autoencoder based online telephony fraud detection. Digit. Commun. Networks 10(1): 158-167 (2024) - [j70]Fabrício Ceschin, Marcus Botacin, Albert Bifet, Bernhard Pfahringer, Luiz S. Oliveira, Heitor Murilo Gomes, André Grégio:
Machine Learning (In) Security: A Stream of Problems. DTRAP 5(1): 9:1-9:32 (2024) - [j69]Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
Gradient boosted trees for evolving data streams. Mach. Learn. 113(5): 3325-3352 (2024) - [c160]Ayman Chaouki, Jesse Read, Albert Bifet:
Online Learning of Decision Trees with Thompson Sampling. AISTATS 2024: 2944-2952 - [c159]Nilesh Verma, Albert Bifet, Bernhard Pfahringer, Maroua Bahri:
ASML: A Scalable and Efficient AutoML Solution for Data Streams. AutoML 2024: 11/1-26 - [c158]Reginaldo Luna, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Heitor Murilo Gomes, Hermes Senger:
Mini-batching with Fused Training and Testing for Data Streams Processing on the Edge. CF 2024 - [c157]Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Giacomo Boracchi:
Online Isolation Forest. ICML 2024 - [c156]Yun Sing Koh, Albert Bifet, Karin R. Bryan, Guilherme Weigert Cassales, Olivier Graffeuille, Nick Jin Sean Lim, Phil Mourot, Ding Ning, Bernhard Pfahringer, Varvara Vetrova, Heitor Murilo Gomes:
Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme. IJCAI 2024: 7314-7322 - [c155]Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet, Yun Sing Koh:
Recurrent Concept Drifts on Data Streams. IJCAI 2024: 8029-8037 - [c154]Jack Julian, Yun Sing Koh, Albert Bifet:
Sketch-Based Replay Projection for Continual Learning. KDD 2024: 1325-1335 - [c153]Heitor Murilo Gomes, Albert Bifet:
Practical Machine Learning for Streaming Data. KDD 2024: 6418-6419 - [c152]Yibin Sun, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
Adaptive Prediction Interval for Data Stream Regression. PAKDD (3) 2024: 130-141 - [c151]Yibin Sun, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet:
Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis. PRICAI (5) 2024: 91-97 - [e27]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14941, Springer 2024, ISBN 978-3-031-70340-9 [contents] - [e26]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14942, Springer 2024, ISBN 978-3-031-70343-0 [contents] - [e25]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part III. Lecture Notes in Computer Science 14943, Springer 2024, ISBN 978-3-031-70351-5 [contents] - [e24]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IV. Lecture Notes in Computer Science 14944, Springer 2024, ISBN 978-3-031-70358-4 [contents] - [e23]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part V. Lecture Notes in Computer Science 14945, Springer 2024, ISBN 978-3-031-70361-4 [contents] - [e22]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VI. Lecture Notes in Computer Science 14946, Springer 2024, ISBN 978-3-031-70364-5 [contents] - [e21]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VII. Lecture Notes in Computer Science 14947, Springer 2024, ISBN 978-3-031-70367-6 [contents] - [e20]Albert Bifet, Povilas Daniusis, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Kai Puolamäki, Indre Zliobaite:
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. Lecture Notes in Computer Science 14948, Springer 2024, ISBN 978-3-031-70370-6 [contents] - [e19]Albert Bifet, Tomas Krilavicius, Ioanna Miliou, Slawomir Nowaczyk:
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. Lecture Notes in Computer Science 14949, Springer 2024, ISBN 978-3-031-70377-5 [contents] - [e18]Albert Bifet, Tomas Krilavicius, Ioanna Miliou, Slawomir Nowaczyk:
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. Lecture Notes in Computer Science 14950, Springer 2024, ISBN 978-3-031-70380-5 [contents] - [i45]Ayman Chaouki, Jesse Read, Albert Bifet:
Online Learning of Decision Trees with Thompson Sampling. CoRR abs/2404.06403 (2024) - [i44]Cedric Kulbach, Lucas Cazzonelli, Hoang-Anh Ngo, Minh-Huong Le Nguyen, Albert Bifet:
A Retrospective of the Tutorial on Opportunities and Challenges of Online Deep Learning. CoRR abs/2405.17222 (2024) - [i43]Ayman Chaouki, Jesse Read, Albert Bifet:
Branches: A Fast Dynamic Programming and Branch & Bound Algorithm for Optimal Decision Trees. CoRR abs/2406.02175 (2024) - [i42]Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams. CoRR abs/2408.09324 (2024) - [i41]Yibin Sun, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet:
Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis. CoRR abs/2408.16187 (2024) - [i40]Léa Cassé, Bernhard Pfahringer, Albert Bifet, Frédéric Magniette:
Optimizing Hyperparameters for Quantum Data Re-Uploaders in Calorimetric Particle Identification. CoRR abs/2412.12397 (2024) - 2023
- [j68]Minh-Huong Le Nguyen, Fabien Turgis, Pierre-Emmanuel Fayemi, Albert Bifet:
Exploring the potentials of online machine learning for predictive maintenance: a case study in the railway industry. Appl. Intell. 53(24): 29758-29780 (2023) - [j67]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) - [j66]Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Vítor Cerqueira, Albert Bifet:
Towards time-evolving analytics: Online learning for time-dependent evolving data streams. Data Sci. 6(1-2): 1-16 (2023) - [j65]Paulo Cortez, Albert Bifet:
Editorial: Seventh special issue on Knowledge Discovery and Business Intelligence. Expert Syst. J. Knowl. Eng. 40(10) (2023) - [j64]Jesus Antonanzas, Yunzhe Jia, Eibe Frank, Albert Bifet, Bernhard Pfahringer:
teex: A toolbox for the evaluation of explanations. Neurocomputing 555: 126642 (2023) - [j63]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) - [j62]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) - [j61]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) - [j60]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) - [c150]Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Choosing the Right Time to Learn Evolving Data Streams. IEEE Big Data 2023: 5156-5165 - [c149]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 - [c148]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 - [c147]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 - [c146]Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet:
FALL: A Modular Adaptive Learning Platform for Streaming Data. ICDE 2023: 3619-3622 - [c145]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 - [c144]Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
Survey on Online Streaming Continual Learning. IJCAI 2023: 6628-6637 - [c143]Zichong Wang, Charles Wallace, Albert Bifet, Xin Yao, Wenbin Zhang:
FG2AN: Fairness-Aware Graph Generative Adversarial Networks. ECML/PKDD (2) 2023: 259-275 - [c142]Cedric Kulbach, Lucas Cazzonelli, Hoang-Anh Ngo, Minh-Huong Le Nguyen, Albert Bifet:
A Retrospective of the Tutorial on Opportunities and Challenges of Online Deep Learning. PKDD/ECML Workshops (1) 2023: 359-372 - [c141]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 - [c140]Martha I. 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 - [e17]Albert Bifet, Ana Carolina Lorena, Rita P. Ribeiro, João Gama, Pedro H. Abreu:
Discovery Science - 26th International Conference, DS 2023, Porto, Portugal, October 9-11, 2023, Proceedings. Lecture Notes in Computer Science 14276, Springer 2023, ISBN 978-3-031-45274-1 [contents] - [e16]João Vinagre, Marie Al-Ghossein, Ladislav Peska, Alípio Mário Jorge, Albert Bifet:
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. CEUR Workshop Proceedings 3549, CEUR-WS.org 2023 [contents] - [e15]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. 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, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
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. Communications in Computer and Information Science 1752, Springer 2023, ISBN 978-3-031-23617-4 [contents] - [e14]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. 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, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
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. Communications in Computer and Information Science 1753, Springer 2023, ISBN 978-3-031-23632-7 [contents] - [i39]Zichong Wang, Nripsuta Saxena, Tongjia Yu, Sneha Karki, Tyler Zetty, Israat Haque, Shan Zhou, Dukka Kc, Ian Stockwell, Albert Bifet, Wenbin Zhang:
Preventing Discriminatory Decision-making in Evolving Data Streams. CoRR abs/2302.08017 (2023) - [i38]Nedeljko Radulovic, Albert Bifet, Fabian M. Suchanek:
BELLA: Black box model Explanations by Local Linear Approximations. CoRR abs/2305.11311 (2023) - [i37]Anton Lee, Yaqian Zhang, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning. CoRR abs/2310.20052 (2023) - 2022
- [j59]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) - [j58]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) - [j57]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) - [j56]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) - [j55]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) - [j54]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) - [j53]Natalia Mordvanyuk, Beatriz López, Albert Bifet:
TA4L: Efficient temporal abstraction of multivariate time series. Knowl. Based Syst. 244: 108554 (2022) - [j52]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) - [j51]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) - [j50]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) - [c139]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 - [c138]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 - [c137]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 - [c136]Nuwan Gunasekara, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Adaptive Neural Networks for Online Domain Incremental Continual Learning. DS 2022: 89-103 - [c135]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 - [c134]Nuwan Gunasekara, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Adaptive Online Domain Incremental Continual Learning. ICANN (1) 2022: 491-502 - [c133]Thomas Guyet, Wenbin Zhang, Albert Bifet:
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrences. ICCS (1) 2022: 460-472 - [c132]Dihia Boulegane, Vitor Cerquiera, Albert Bifet:
Adaptive Model Compression of Ensembles for Evolving Data Streams Forecasting. IJCNN 2022: 1-8 - [c131]Nuwan Gunasekara, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet:
Online Hyperparameter Optimization for Streaming Neural Networks. IJCNN 2022: 1-9 - [c130]Jacob Montiel, Hoang-Anh Ngo, Minh-Huong Le Nguyen, Albert Bifet:
Online Clustering: Algorithms, Evaluation, Metrics, Applications and Benchmarking. KDD 2022: 4808-4809 - [c129]Peng Yu, Albert Bifet, Jesse Read, Chao Xu:
Linear tree shap. NeurIPS 2022 - [c128]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 - [c127]Cedric Kulbach, Jacob Montiel, Maroua Bahri, Marco Heyden, Albert Bifet:
Evolution-Based Online Automated Machine Learning. PAKDD (1) 2022: 472-484 - [c126]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 - [c125]Zijing Zhang, Vimal Kumar, Michael Mayo, Albert Bifet:
Assessing Vulnerability from Its Description. UbiSec 2022: 129-143 - [e13]João Vinagre, Marie Al-Ghossein, Alípio Mário Jorge, Albert Bifet, Ladislav Peska:
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. CEUR Workshop Proceedings 3303, CEUR-WS.org 2022 [contents] - [i36]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet:
Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling - ORSUM 2021. CoRR abs/2201.05156 (2022) - [i35]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. CoRR abs/2201.06205 (2022) - [i34]Thomas Guyet, Wenbin Zhang, Albert Bifet:
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrence. CoRR abs/2201.11650 (2022) - [i33]Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, João Gama, Georges Hébrail, Vincent Lemaire, Pierre-François Marteau:
Open challenges for Machine Learning based Early Decision-Making research. CoRR abs/2204.13111 (2022) - [i32]Eva García-Martín, Albert Bifet, Niklas Lavesson, Rikard König, Henrik Linusson:
Green Accelerated Hoeffding Tree. CoRR abs/2205.03184 (2022) - [i31]Peng Yu, Chao Xu, Albert Bifet, Jesse Read:
Linear TreeShap. CoRR abs/2209.08192 (2022) - [i30]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. CoRR abs/2209.13917 (2022) - 2021
- [j49]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) - [j48]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) - [j47]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) - [j46]Natalia Mordvanyuk, Beatriz López, Albert Bifet:
vertTIRP: Robust and efficient vertical frequent time interval-related pattern mining. Expert Syst. Appl. 168: 114276 (2021) - [j45]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) - [j44]Eva García-Martín, Albert Bifet, Niklas Lavesson:
Energy modeling of Hoeffding tree ensembles. Intell. Data Anal. 25(1): 81-104 (2021) - [j43]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) - [j42]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) - [j41]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) - [j40]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) - [c124]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 - [c123]Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Kalman Filtering for Learning with Evolving Data Streams. IEEE BigData 2021: 5337-5346 - [c122]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 - [c121]Maroua Bahri, Albert Bifet:
Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams. DS 2021: 122-137 - [c120]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 - [c119]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 - [c118]Nedeljko Radulovic, Albert Bifet, Fabian M. Suchanek:
Confident Interpretations of Black Box Classifiers. IJCNN 2021: 1-8 - [c117]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 - [c116]Wenbin Zhang, Albert Bifet, Xiangliang Zhang, Jeremy C. Weiss, Wolfgang Nejdl:
FARF: A Fair and Adaptive Random Forests Classifier. PAKDD (2) 2021: 245-256 - [c115]Yunzhe Jia, Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Jin Sean Lim:
Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality. ECML/PKDD (2) 2021: 699-714 - [c114]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet:
ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling. RecSys 2021: 792-793 - [c113]Einav Peretz-Andersson, Niklas Lavesson, Albert Bifet, Patrick Mikalef:
AI Transformation in the Public Sector: Ongoing Research. SAIS 2021: 1-4 - [i29]Vítor Cerqueira, Heitor Murilo Gomes, Albert Bifet, Luís Torgo:
STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection. CoRR abs/2103.00903 (2021) - [i28]Md. Mahbub Alam, Luís Torgo, Albert Bifet:
A Survey on Spatio-temporal Data Analytics Systems. CoRR abs/2103.09883 (2021) - [i27]Vítor Cerqueira, Luís Torgo, Carlos Soares, Albert Bifet:
Model Compression for Dynamic Forecast Combination. CoRR abs/2104.01830 (2021) - [i26]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. CoRR abs/2106.09170 (2021) - [i25]Wenbin Zhang, Albert Bifet, Xiangliang Zhang, Jeremy C. Weiss, Wolfgang Nejdl:
FARF: A Fair and Adaptive Random Forests Classifier. CoRR abs/2108.07403 (2021) - [i24]Jesus Antonanzas, Marta Arias, Albert Bifet:
Sketches for Time-Dependent Machine Learning. CoRR abs/2108.11923 (2021) - [i23]Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Improving the performance of bagging ensembles for data streams through mini-batching. CoRR abs/2112.09834 (2021) - 2020
- [j39]Albert Bifet, João Gama:
IoT data stream analytics. Ann. des Télécommunications 75(9-10): 491-492 (2020) - [j38]Maciej Grzenda, Heitor Murilo Gomes, Albert Bifet:
Delayed labelling evaluation for data streams. Data Min. Knowl. Discov. 34(5): 1237-1266 (2020) - [j37]Paulo Cortez, Albert Bifet:
Fifth special issue on knowledge discovery and business intelligence. Expert Syst. J. Knowl. Eng. 37(6) (2020) - [j36]Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet, Meriem Bouzbila:
Sampling informative patterns from large single networks. Future Gener. Comput. Syst. 106: 653-658 (2020) - [j35]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) - [j34]Yiyan Qi, Jiefeng Cheng, Xiaojun Chen, Reynold Cheng, Albert Bifet, Pinghui Wang:
Discriminative Streaming Network Embedding. Knowl. Based Syst. 190: 105138 (2020) - [j33]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) - [j32]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) - [c112]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 - [c111]Maroua Bahri, Bruno Veloso, Albert Bifet, João Gama:
AutoML for Stream k-Nearest Neighbors Classification. IEEE BigData 2020: 597-602 - [c110]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 - [c109]Wenbin Zhang, Albert Bifet:
FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier. DS 2020: 175-189 - [c108]Vítor Cerqueira, Heitor Murilo Gomes, Albert Bifet:
Unsupervised Concept Drift Detection Using a Student-Teacher Approach. DS 2020: 190-204 - [c107]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 - [c106]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 - [c105]Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Incremental Rebalancing Learning on Evolving Data Streams. ICDM (Workshops) 2020: 844-850 - [c104]Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Fast Incremental Naïve Bayes with Kalman Filtering. ICDM (Workshops) 2020: 883-889 - [c103]Maroua Bahri, Bernhard Pfahringer, Albert Bifet, Silviu Maniu:
Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams. IDA 2020: 40-53 - [c102]Maroua Bahri, Albert Bifet, Silviu Maniu, Heitor Murilo Gomes:
Survey on Feature Transformation Techniques for Data Streams. IJCAI 2020: 4796-4802 - [c101]Maroua Bahri, Heitor Murilo Gomes, Albert Bifet, Silviu Maniu:
CS-ARF: Compressed Adaptive Random Forests for Evolving Data Stream Classification. IJCNN 2020: 1-8 - [c100]Heitor Murilo Gomes, Jacob Montiel, Saulo Martiello Mastelini, Bernhard Pfahringer, Albert Bifet:
On Ensemble Techniques for Data Stream Regression. IJCNN 2020: 1-8 - [c99]Maciej Grzenda, Heitor Murilo Gomes, Albert Bifet:
Performance measures for evolving predictions under delayed labelling classification. IJCNN 2020: 1-8 - [c98]Viktor Losing, Barbara Hammer, Heiko Wersing, Albert Bifet:
Randomizing the Self-Adjusting Memory for Enhanced Handling of Concept Drift. IJCNN 2020: 1-8 - [c97]Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet:
Adaptive XGBoost for Evolving Data Streams. IJCNN 2020: 1-8 - [c96]Matthias Carnein, Heike Trautmann, Albert Bifet, Bernhard Pfahringer:
confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms. LION 2020: 80-95 - [c95]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 - [c94]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet:
ORSUM - Workshop on Online Recommender Systems and User Modeling. RecSys 2020: 619-620 - [e12]Albert Bifet, Michele Berlingerio, João Gama, Jesse Read, Ana Rita Nogueira:
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. CEUR Workshop Proceedings 2579, CEUR-WS.org 2020 [contents] - [e11]João Gama, Sepideh Pashami, Albert Bifet, Moamar Sayed Mouchaweh, Holger Fröning, Franz Pernkopf, Gregor Schiele, Michaela Blott:
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. Communications in Computer and Information Science 1325, Springer 2020, ISBN 978-3-030-66769-6 [contents] - [e10]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet:
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. CEUR Workshop Proceedings 2715, CEUR-WS.org 2020 [contents] - [i22]Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet:
Adaptive XGBoost for Evolving Data Streams. CoRR abs/2005.07353 (2020) - [i21]Nicolas Kourtellis, Herodotos Herodotou, Maciej Grzenda, Piotr Wawrzyniak, Albert Bifet:
S2CE: A Hybrid Cloud and Edge Orchestrator for Mining Exascale Distributed Streams. CoRR abs/2007.01260 (2020) - [i20]Jesus L. Lobo, Javier Del Ser, Eneko Osaba, Albert Bifet, Francisco Herrera:
CURIE: A Cellular Automaton for Concept Drift Detection. CoRR abs/2009.09677 (2020) - [i19]Chaitanya Manapragada, Geoffrey I. Webb, Mahsa Salehi, Albert Bifet:
Emergent and Unspecified Behaviors in Streaming Decision Trees. CoRR abs/2010.08199 (2020) - [i18]Chaitanya Manapragada, Heitor Murilo Gomes, Mahsa Salehi, Albert Bifet, Geoffrey I. Webb:
An Eager Splitting Strategy for Online Decision Trees. CoRR abs/2010.10935 (2020) - [i17]Fabricio Ceschin, Heitor Murilo Gomes, Marcus Botacin, Albert Bifet, Bernhard Pfahringer, Luiz S. Oliveira, André Grégio:
Machine Learning (In) Security: A Stream of Problems. CoRR abs/2010.16045 (2020) - [i16]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. CoRR abs/2012.04740 (2020)
2010 – 2019
- 2019
- [j31]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) - [j30]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) - [j29]Rodrigo Fernandes de Mello, Chaitanya Manapragada, Albert Bifet:
Measuring the Shattering coefficient of Decision Tree models. Expert Syst. Appl. 137: 443-452 (2019) - [j28]Robert Anderson, Yun Sing Koh, Gillian Dobbie, Albert Bifet:
Recurring concept meta-learning for evolving data streams. Expert Syst. Appl. 138 (2019) - [j27]Abhik Ray, Lawrence B. Holder, Albert Bifet:
Efficient frequent subgraph mining on large streaming graphs. Intell. Data Anal. 23(1): 103-132 (2019) - [j26]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) - [j25]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) - [j24]Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem:
Correction to: Adaptive random forests for evolving data stream classification. Mach. Learn. 108(10): 1877-1878 (2019) - [j23]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 Explor. 21(2): 6-22 (2019) - [c93]Minh-Huong Le Nguyen, Heitor Murilo Gomes, Albert Bifet:
Semi-supervised Learning over Streaming Data using MOA. IEEE BigData 2019: 553-562 - [c92]Heitor Murilo Gomes, Rodrigo Fernandes de Mello, Bernhard Pfahringer, Albert Bifet:
Feature Scoring using Tree-Based Ensembles for Evolving Data Streams. IEEE BigData 2019: 761-769 - [c91]Dihia Boulegane, Albert Bifet, Giyyarpuram Madhusudan:
Arbitrated Dynamic Ensemble with Abstaining for Time-Series Forecasting on Data Streams. IEEE BigData 2019: 1040-1045 - [c90]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. IEEE BigData 2019: 3493-3497 - [c89]Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
Adaptive Algorithms for Estimating Betweenness and k-path Centralities. CIKM 2019: 1231-1240 - [c88]Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet:
Metropolis-Hastings Algorithms for Estimating Betweenness Centrality. EDBT 2019: 686-689 - [c87]Albert Bifet, Barbara Hammer, Frank-Michael Schleif:
Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets. ESANN 2019 - [c86]Heitor Murilo Gomes, Jesse Read, Albert Bifet:
Streaming Random Patches for Evolving Data Stream Classification. ICDM 2019: 240-249 - [c85]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 - [c84]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 - [c83]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 - [c82]Matthias Carnein, Heike Trautmann, Albert Bifet, Bernhard Pfahringer:
Towards Automated Configuration of Stream Clustering Algorithms. PKDD/ECML Workshops (1) 2019: 137-143 - [c81]João Vinagre, Alípio Mário Jorge, Albert Bifet, Marie Al-Ghossein:
ORSUM 2019 2nd workshop on online recommender systems and user modeling. RecSys 2019: 562-563 - [c80]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 - [e9]Anna Monreale, Carlos Alzate, Michael Kamp, Yamuna Krishnamurthy, Daniel Paurat, Moamar Sayed Mouchaweh, Albert Bifet, João Gama, Rita P. Ribeiro:
ECML PKDD 2018 Workshops - DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers. Communications in Computer and Information Science 967, Springer 2019, ISBN 978-3-030-14879-9 [contents] - [e8]Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian M. Molloy, Maria-Irina Nicolae, Mathieu Sinn:
ECML PKDD 2018 Workshops - Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings. Lecture Notes in Computer Science 11329, Springer 2019, ISBN 978-3-030-13452-5 [contents] - [e7]João Vinagre, Alípio Mário Jorge, Albert Bifet, Marie Al-Ghossein:
2nd Workshop on Online Recommender Systems and User Modeling, ORSUM@RecSys 2019, 19 September 2019, Copenhagen, Denmark. Proceedings of Machine Learning Research 109, PMLR 2019 [contents] - [i15]Diego Marrón, Eduard Ayguadé, José Ramon Herrero, Albert Bifet:
Resource-aware Elastic Swap Random Forest for Evolving Data Streams. CoRR abs/1905.05881 (2019) - [i14]Robert Anderson, Yun Sing Koh, Gillian Dobbie, Albert Bifet:
Recurring Concept Meta-learning for Evolving Data Streams. CoRR abs/1905.08848 (2019) - [i13]Jesus L. Lobo, Izaskun Oregi, Albert Bifet, Javier Del Ser:
Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning. CoRR abs/1908.08018 (2019) - [i12]Jesus L. Lobo, Javier Del Ser, Albert Bifet, Nikola K. Kasabov:
Spiking Neural Networks and Online Learning: An Overview and Perspectives. CoRR abs/1908.08019 (2019) - [i11]Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Rebalancing Learning on Evolving Data Streams. CoRR abs/1911.07361 (2019) - 2018
- [j22]Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
Discriminative Distance-Based Network Indices with Application to Link Prediction. Comput. J. 61(7): 998-1014 (2018) - [j21]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) - [j20]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) - [c79]Maroua Bahri, Silviu Maniu, Albert Bifet:
A Sketch-Based Naive Bayes Algorithms for Evolving Data Streams. IEEE BigData 2018: 604-613 - [c78]Jacob Montiel, Albert Bifet, Viktor Losing, Jesse Read, Talel Abdessalem:
Learning Fast and Slow: A Unified Batch/Stream Framework. IEEE BigData 2018: 1065-1072 - [c77]Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
An In-depth Comparison of Group Betweenness Centrality Estimation Algorithms. IEEE BigData 2018: 2104-2113 - [c76]Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
DyBED: An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs. IEEE BigData 2018: 2114-2123 - [c75]Albert Bifet, Jesse Read:
Ubiquitous Artificial Intelligence and Dynamic Data Streams. DEBS 2018: 1-6 - [c74]Heitor Murilo Gomes, Jean Paul Barddal, Luis Eduardo Boiko Ferreira, Albert Bifet:
Adaptive random forests for data stream regression. ESANN 2018 - [c73]Tian Guo, Albert Bifet, Nino Antulov-Fantulin:
Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders. ICDM 2018: 989-994 - [c72]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 - [c71]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 - [c70]Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem:
Scalable Model-Based Cascaded Imputation of Missing Data. PAKDD (3) 2018: 64-76 - [c69]Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs. PAKDD (3) 2018: 752-764 - [c68]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 - [i10]Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet:
Large-Scale Learning from Data Streams with Apache SAMOA. CoRR abs/1805.11477 (2018) - [i9]Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem:
Scikit-Multiflow: A Multi-output Streaming Framework. CoRR abs/1807.04662 (2018) - [i8]Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
Novel Adaptive Algorithms for Estimating Betweenness, Coverage and k-path Centralities. CoRR abs/1810.10094 (2018) - 2017
- [j19]Heitor Murilo Gomes, Jean Paul Barddal, Fabrício Enembreck, Albert Bifet:
A Survey on Ensemble Learning for Data Stream Classification. ACM Comput. Surv. 50(2): 23:1-23:36 (2017) - [j18]Diego Marron, Jesse Read, Albert Bifet, Nacho Navarro:
Data stream classification using random feature functions and novel method combinations. J. Syst. Softw. 127: 195-204 (2017) - [j17]Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem:
Adaptive random forests for evolving data stream classification. Mach. Learn. 106(9-10): 1469-1495 (2017) - [c67]Diego Marron, Eduard Ayguadé, José R. Herrero, Jesse Read, Albert Bifet:
Low-latency multi-threaded ensemble learning for dynamic big data streams. IEEE BigData 2017: 223-232 - [c66]Jacob Montiel, Albert Bifet, Talel Abdessalem:
Predicting over-indebtedness on batch and streaming data. IEEE BigData 2017: 1504-1513 - [c65]Albert Bifet:
Classifier Concept Drift Detection and the Illusion of Progress. ICAISC (2) 2017: 715-725 - [c64]Pierre-Xavier Loeffel, Albert Bifet, Christophe Marsala, Marcin Detyniecki:
Droplet Ensemble Learning on Drifting Data Streams. IDA 2017: 210-222 - [c63]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 - [c62]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 - [e6]Moamar Sayed Mouchaweh, Albert Bifet, Hamid Bouchachia, João Gama, Rita Paula Ribeiro:
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. CEUR Workshop Proceedings 1958, CEUR-WS.org 2017 [contents] - [i7]Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
Discriminative Distance-Based Network Indices and the Tiny-World Property. CoRR abs/1703.06227 (2017) - [i6]Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet:
Metropolis-Hastings Algorithms for Estimating Betweenness Centrality in Large Networks. CoRR abs/1704.07351 (2017) - [i5]Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem:
Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs. CoRR abs/1708.08739 (2017) - 2016
- [j16]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. Telecommun. Syst. 63(2): 191-204 (2016) - [j15]João Duarte, João Gama, Albert Bifet:
Adaptive Model Rules From High-Speed Data Streams. ACM Trans. Knowl. Discov. Data 10(3): 30:1-30:22 (2016) - [c61]Diego Marron, Jesse Read, Albert Bifet, Talel Abdessalem, Eduard Ayguadé, José R. Herrero:
Echo State Hoeffding Tree Learning. ACML 2016: 382-397 - [c60]Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet, Arinto Murdopo:
VHT: Vertical hoeffding tree. IEEE BigData 2016: 915-922 - [c59]Gianmarco De Francisci Morales, Albert Bifet, Latifur Khan, João Gama, Wei Fan:
IoT Big Data Stream Mining. KDD 2016: 2119-2120 - [c58]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 - [c57]Michael Mayo, Albert Bifet:
Deferral classification of evolving temporal dependent data streams. SAC 2016: 952-954 - [c56]Albert Bifet:
Mining Internet of Things (IoT) Big Data Streams. SIMBig 2016: 15-16 - [c55]Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet:
Analyzing Big Data Streams with Apache SAMOA. MSM@WWW,MUSE@PKDD/ECML 2016: 44-67 - [e5]Wei Fan, Albert Bifet, Jesse Read, Qiang Yang, Philip S. Yu:
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. JMLR Workshop and Conference Proceedings 53, JMLR.org 2016 [contents] - [i4]Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet, Arinto Murdopo:
VHT: Vertical Hoeffding Tree. CoRR abs/1607.08325 (2016) - 2015
- [j14]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) - [j13]Gianmarco De Francisci Morales, Albert Bifet:
SAMOA: scalable advanced massive online analysis. J. Mach. Learn. Res. 16: 149-153 (2015) - [j12]Indre Zliobaite, Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes:
Evaluation methods and decision theory for classification of streaming data with temporal dependence. Mach. Learn. 98(3): 455-482 (2015) - [c54]Albert Bifet, Silviu Maniu, Jianfeng Qian, Guangjian Tian, Cheng He, Wei Fan:
StreamDM: Advanced Data Mining in Spark Streaming. ICDM Workshops 2015: 1608-1611 - [c53]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 - [c52]Wei Fan, Albert Bifet, Qiang Yang, Philip S. Yu:
Preface. BigMine 2015: 4 - [c51]Albert Bifet, Gianmarco De Francisci Morales, Jesse Read, Geoff Holmes, Bernhard Pfahringer:
Efficient Online Evaluation of Big Data Stream Classifiers. KDD 2015: 59-68 - [c50]Albert Bifet:
Mining Big Data Streams with Apache SAMOA. MUSE@PKDD/ECML 2015: 55 - [c49]David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet:
Drift Detection Using Stream Volatility. ECML/PKDD (1) 2015: 417-432 - [c48]Jesse Read, Fernando Pérez-Cruz, Albert Bifet:
Deep learning in partially-labeled data streams. SAC 2015: 954-959 - [c47]Albert Bifet:
Real-Time Big Data Stream Analytics. SIMBig 2015: 13-14 - [c46]Jesse Read, Albert Bifet:
Data Stream Classification Using Random Feature Functions and Novel Method Combinations. TrustCom/BigDataSE/ISPA (2) 2015: 211-216 - [e4]Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavaldà, Dino Pedreschi, Francesco Bonchi, Jaime S. Cardoso, Myra Spiliopoulou:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III. Lecture Notes in Computer Science 9286, Springer 2015, ISBN 978-3-319-23460-1 [contents] - [i3]Sripirakas Sakthithasan, Russel Pears, Albert Bifet, Bernhard Pfahringer:
Use of Ensembles of Fourier Spectra in Capturing Recurrent Concepts in Data Streams. CoRR abs/1504.06366 (2015) - [i2]Diego Marron, Jesse Read, Albert Bifet, Nacho Navarro:
Data Stream Classification using Random Feature Functions and Novel Method Combinations. CoRR abs/1511.00971 (2015) - 2014
- [j11]João Gama, Indre Zliobaite, Albert Bifet, Mykola Pechenizkiy, Abdelhamid Bouchachia:
A survey on concept drift adaptation. ACM Comput. Surv. 46(4): 44:1-44:37 (2014) - [j10]Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoffrey Holmes:
Active Learning With Drifting Streaming Data. IEEE Trans. Neural Networks Learn. Syst. 25(1): 27-39 (2014) - [c45]Anh Thu Vu, Gianmarco De Francisci Morales, João Gama, Albert Bifet:
Distributed Adaptive Model Rules for mining big data streams. IEEE BigData 2014: 345-353 - [c44]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 - [c43]Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet:
Détection de changements dans des flots de données qualitatives. EGC 2014: 517-520 - [c42]Brandon Parker, Latifur Khan, Albert Bifet:
Incremental Ensemble Classifier Addressing Non-stationary Fast Data Streams. ICDM Workshops 2014: 716-723 - [c41]Jesse Read, Antti Puurula, Albert Bifet:
Multi-label Classification with Meta-Labels. ICDM 2014: 941-946 - [c40]Albert Bifet, Gianmarco De Francisci Morales:
Big Data Stream Learning with SAMOA. ICDM Workshops 2014: 1199-1202 - [c39]Wei Fan, Albert Bifet, Qiang Yang, Philip S. Yu:
Preface. BigMine 2014 - [c38]Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet:
Change detection in categorical evolving data streams. SAC 2014: 792-797 - [e3]Wei Fan, Albert Bifet, Qiang Yang, Philip S. Yu:
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. JMLR Workshop and Conference Proceedings 36, JMLR.org 2014 [contents] - [i1]Antti Puurula, Jesse Read, Albert Bifet:
Kaggle LSHTC4 Winning Solution. CoRR abs/1405.0546 (2014) - 2013
- [j9]Albert Bifet:
Mining Big Data in Real Time. Informatica (Slovenia) 37(1): 15-20 (2013) - [c37]Massimo Quadrana, Albert Bifet, Ricard Gavaldà:
An Efficient Closed Frequent Itemset Miner for the Moa Stream Mining System. CCIA 2013: 203-212 - [c36]Dino Ienco, Albert Bifet, Indre Zliobaite, Bernhard Pfahringer:
Clustering Based Active Learning for Evolving Data Streams. Discovery Science 2013: 79-93 - [c35]Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes, Indre Zliobaite:
CD-MOA: Change Detection Framework for Massive Online Analysis. IDA 2013: 92-103 - [c34]Konstantin Kutzkov, Albert Bifet, Francesco Bonchi, Aristides Gionis:
STRIP: stream learning of influence probabilities. KDD 2013: 275-283 - [c33]Albert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, Geoff Holmes:
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them. ECML/PKDD (1) 2013: 465-479 - [c32]Albert Bifet, Bernhard Pfahringer, Jesse Read, Geoff Holmes:
Efficient data stream classification via probabilistic adaptive windows. SAC 2013: 801-806 - [e2]Wei Fan, Albert Bifet, Qiang Yang, Philip S. Yu:
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. ACM 2013, ISBN 978-1-4503-2324-6 [contents] - 2012
- [j8]Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer:
Scalable and efficient multi-label classification for evolving data streams. Mach. Learn. 88(1-2): 243-272 (2012) - [j7]Indre Zliobaite, Albert Bifet, Mohamed Medhat Gaber, Bogdan Gabrys, João Gama, Leandro L. Minku, Katarzyna Musial:
Next challenges for adaptive learning systems. SIGKDD Explor. 14(1): 48-55 (2012) - [j6]Wei Fan, Albert Bifet:
Mining big data: current status, and forecast to the future. SIGKDD Explor. 14(2): 1-5 (2012) - [j5]Albert Bifet, Eibe Frank, Geoff Holmes, Bernhard Pfahringer:
Ensembles of Restricted Hoeffding Trees. ACM Trans. Intell. Syst. Technol. 3(2): 30:1-30:20 (2012) - [c31]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 - [c30]Jesse Read, Albert Bifet, Bernhard Pfahringer, Geoff Holmes:
Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data. IDA 2012: 313-323 - [e1]Wei Fan, Albert Bifet, Qiang Yang, Philip S. Yu:
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. ACM 2012, ISBN 978-1-4503-1547-0 [contents] - 2011
- [j4]Albert Bifet, Ricard Gavaldà:
Mining frequent closed trees in evolving data streams. Intell. Data Anal. 15(1): 29-48 (2011) - [c29]Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer:
MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data. Discovery Science 2011: 46-60 - [c28]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 - [c27]Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Ricard Gavaldà:
Mining frequent closed graphs on evolving data streams. KDD 2011: 591-599 - [c26]Hardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer:
An effective evaluation measure for clustering on evolving data streams. KDD 2011: 868-876 - [c25]Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoff Holmes:
Active Learning with Evolving Streaming Data. ECML/PKDD (3) 2011: 597-612 - [c24]Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl:
MOA: A Real-Time Analytics Open Source Framework. ECML/PKDD (3) 2011: 617-620 - [c23]Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Ricard Gavaldà:
Detecting Sentiment Change in Twitter Streaming Data. WAPA 2011: 5-11 - [c22]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. WAPA 2011: 12-18 - [c21]Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer:
Streaming Multi-label Classification. WAPA 2011: 19-25 - [c20]Indre Zliobaite, Albert Bifet, Geoff Holmes, Bernhard Pfahringer:
MOA Concept Drift Active Learning Strategies for Streaming Data. WAPA 2011: 48-55 - 2010
- [b2]Albert Bifet:
Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams. Frontiers in Artificial Intelligence and Applications 207, IOS Press 2010, ISBN 978-1-60750-090-2, pp. 1-212 - [j3]Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer:
MOA: Massive Online Analysis. J. Mach. Learn. Res. 11: 1601-1604 (2010) - [j2]José L. Balcázar, Albert Bifet, Antoni Lozano:
Mining frequent closed rooted trees. Mach. Learn. 78(1-2): 1-33 (2010) - [c19]Albert Bifet, Eibe Frank:
Sentiment Knowledge Discovery in Twitter Streaming Data. Discovery Science 2010: 1-15 - [c18]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 - [c17]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 - [c16]Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Eibe Frank:
Fast Perceptron Decision Tree Learning from Evolving Data Streams. PAKDD (2) 2010: 299-310 - [c15]Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer:
Leveraging Bagging for Evolving Data Streams. ECML/PKDD (1) 2010: 135-150 - [c14]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. WAPA 2010: 44-50 - [c13]Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer:
Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking. ACML 2010: 225-240
2000 – 2009
- 2009
- [b1]Albert Bifet:
Adaptive Learning and Mining for Data Streams and Frequent Patterns. Polytechnic University of Catalonia, Spain, 2009 - [j1]Albert Bifet:
Adaptive learning and mining for data streams and frequent patterns. SIGKDD Explor. 11(1): 55-56 (2009) - [c12]Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Ricard Gavaldà:
Improving Adaptive Bagging Methods for Evolving Data Streams. ACML 2009: 23-37 - [c11]Albert Bifet, Ricard Gavaldà:
Adaptive Learning from Evolving Data Streams. IDA 2009: 249-260 - [c10]Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Ricard Gavaldà:
New ensemble methods for evolving data streams. KDD 2009: 139-148 - [c9]Albert Bifet, Ricard Gavaldà:
Adaptive XML Tree Mining on Evolving Data Streams. MLG/SRL@ILP 2009 - [c8]Albert Bifet, Ricard Gavaldà:
Adaptive XML Tree Classification on Evolving Data Streams. ECML/PKDD (1) 2009: 147-162 - 2008
- [c7]José L. Balcázar, Albert Bifet, Antoni Lozano:
Mining Implications from Lattices of Closed Trees. EGC 2008: 373-384 - [c6]Albert Bifet, Ricard Gavaldà:
Mining adaptively frequent closed unlabeled rooted trees in data streams. KDD 2008: 34-42 - 2007
- [c5]José L. Balcázar, Albert Bifet, Antoni Lozano:
Subtree Testing and Closed Tree Mining Through Natural Representations. DEXA Workshops 2007: 499-503 - [c4]José L. Balcázar, Albert Bifet, Antoni Lozano:
Mining Frequent Closed Unordered Trees Through Natural Representations. ICCS 2007: 347-359 - [c3]Albert Bifet, Ricard Gavaldà:
Learning from Time-Changing Data with Adaptive Windowing. SDM 2007: 443-448 - 2006
- [c2]Albert Bifet, Ricard Gavaldà:
Kalman Filters and Adaptive Windows for Learning in Data Streams. Discovery Science 2006: 29-40 - 2005
- [c1]Albert Bifet, Carlos Castillo, Paul-Alexandru Chirita, Ingmar Weber:
An Analysis of Factors Used in Search Engine Ranking. AIRWeb 2005: 48-57
Coauthor Index
[i47] [i46] [j70] [j69] [c158] [c156] [c155] [c153] [c152] [c151] [i41] [j67] [j62] [j60] [c149] [c144] [i37] [j58] [j57] [j55] [j54] [c136] [c134] [c131] [i35] [j43] [j42] [j41] [j40] [c117] [i29] [i26] [i23] [j38] [c112] [c108] [c106] [c102] [c101] [c100] [c99] [i18] [i17] [i16] [j31] [j25] [j24] [j23] [c93] [c92] [c86] [c85] [c84] [c74] [j19] [j17] [c58]
[j73] [j72] [c161] [i47] [i46] [j70] [j69] [c159] [c158] [c157] [c156] [c155] [c152] [c151] [i41] [i40] [j64] [j60] [c149] [c144] [i37] [j57] [j54] [c136] [c134] [c131] [c128] [i35] [i30] [j43] [c117] [c115] [i23] [c112] [c106] [c103] [c100] [c97] [c96] [i22] [i17] [j31] [j25] [j24] [c92] [c82] [j17] [c63] [c58] [j12] [c53] [c51] [i3] [j10] [c43] [c38] [c36] [c35] [c33] [c32] [j8] [j5] [c31] [c30] [c29] [c27] [c26] [c25] [c24] [c23] [c21] [c20] [j3] [c17] [c16] [c15] [c14] [c13] [c12] [c10]
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