Data Science and Mining team (DaSciM)
LIX Laboratory, École Polytechnique.

Publications

See me also on Google Scholar | dblp.

2018

Fei Song, Yanlei Diao, Jesse Read, Arnaud Stiegler, Albert Bifet. EXAD: A System for Explainable Anomaly Detection on Big Data Traces. (Accepted in) 2018 ICDM Demo Session. 2018.

Lukas Kemmer, Henrik von Kleist, Diego María De Grimaudet De Rochebouët, Nikolaos Tziortziotis, Jesse Read. Reinforcement learning for supply chain optimization. EWRL14: European Workshop on Reinforcement Learning. 2018.

Jesse Read, Nikolaos Tziortziotis, Michalis Vazirgiannis. Error-space Representations for Multi-dimensional Data-Streams. Pattern Analysis and Applications. In Press. 2018.

Laurence A. F. Park, Jesse Read. A Blended Metric for Multi-label Optimisation and Evaluation. To appear in Proc. of ECML 2018: 29th European Conference on Machine Learning. 2018.

Albert Bifet, Jesse Read. Ubiquitous Artificial Intelligence and Dynamic Data Streams. In Proc. of DEBS’18: 12th ACM International Conference on Distributed and Event-based Systems. pp 1—6. 2018.

Jacob Montiel, Jesse Read, Albert, Talel Abdessalem. Scalable Model-based Cascaded Imputation of Missing Data. In Proc. of PAKDD 2018: 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining. pp 64—76. 2018.

2017

Jesse Read, Jaakko Hollmén. Multi-label Classification using Labels as Hidden Nodes. ArXiv. 2017.

Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Žitnik, Michelangelo Ceci, Sašo Džeroski, editors. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18—22, 2017, Proceedings, Part III. Lecture Notes in Computer Science 10536, 2017.

Diego Marron, Jesse Read, Albert Bifet, Eduard Ayguadé, José R. Herrero. Low-latency Multi-threaded Ensemble Learning for Dynamic Big Data Streams. In Proc. of IEEE International Conference on Big Data (Big Data 2017). pp 223-232. 2017.

Roelant A. Stegmann, Indrė Žliobaitė, Tuukka Tolvanen, Jaakko Hollmén, Jesse Read. A survey of evaluation methods for personal route and destination prediction from mobility traces. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. Vol. 2(8). pp e1237. 2017.

Heitor M. Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem. Adaptive Random Forests for Evolving Data Stream Classification. Machine Learning Journal. Vol. 106(9-10). pp 1469-1495. 2017.

Luca Martino, Jesse Read, Victor Elvira, Francisco Louzada. Cooperative Parallel Particle Filters for online model selection and applications to Urban Mobility. Digital Signal Processing. Vol. 60(January). pp 172—185. 2017.

Jesse Read, Luca Martino, Jaakko Hollmén. Multi-label Methods for Prediction with Sequential Data. Pattern Recognition. Vol. 63(March). pp 45—55. 2017.

Liisa Kulmala, Jesse Read, Pekka Nöjd, Cyrille B. K. Rathgeber, Henri E. Cuny, Jaakko Hollmén, Harri Mäkinen. Identifying the main drivers for the production and maturation of Scots pine tracheids along a temperature gradient. Agricultural and Forest Meteorology. Vol. 232(January). pp 210—224. 2017.

Diego Marron, Jesse Read, Albert Bifet. Data Stream Classification using Random Feature Functions and Novel Method Combinations. Journal of Systems and Software. Vol. 127(May). pp 195–204. 2017.

2016

Albert Bifet, Jesse Read. Internet de las Cosas: La minería de flujos de datos masivos en tiempo real. Novática (Revista de la Asociación de Técnicos de Informática), Monografía Big Data. Vol. Julio-Octubre(237). pp 24-30. 2016.

Diego Marron, Jesse Read, Albert Bifet, Talel Abdessalem, Eduard Ayguadé, José R. Herrero. Echo State Hoeffding Tree Learning. In Proc. of ACML 2016: The 8th Asian Conference on Machine Learning. pp 382—397. 2016.

Ngurah Agus Sanjaya Er, Jesse Read, Talel Abdessalem, Stephane Bressan. Set Labelling by Example. The 11th International Workshop on Information Search, Integration, and Personalization. 2016.

Jesse Read, Peter Reutemann, Bernhard Pfahringer, Geoff Holmes. MEKA: A Multi-label/Multi-target Extension to Weka. Journal of Machine Learning Research. Vol. 17(21). pp 1—5. 2016.

Jesse Read, Indṙe Žliobaiṫe, Jaakko Hollmén. Labeling sensing data for mobility modeling. Information Systems. Vol. 57(April). pp 207—222. 2016.

2015

Jesse Read, Albert Bifet. Data Stream Classification using Random Feature Functions and Novel Method Combinations. RTStreams2015: The 1st IEEE International Workshop on Real Time Data Stream Analytics held in conjunction with IEEE BigDataSE-15. 2015.

Albert Bifet, Gianmarco De Francisci Morales, Jesse Read, Bernhard Pfahringer, Geoff Holmes. Efficient Online Evaluation of Big Data Stream Classifiers. In Proc. of ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’15). pp 59-68. 2015.

Luca Martino, Jesse Read, David Luengo. Independent Doubly Adaptive Rejection Metropolis Sampling within Gibbs Sampling. Transactions on Signal Processing. Vol. 63(12). pp 3123 - 3138. 2015.

Jesse Read, Fernando Perez-Cruz, Albert Bifet. Deep Learning in Multi-label Data-Streams. In Proc. of SAC 2015: 30th ACM Symposium on Applied Computing. pp 954-959. 2015.

Jesse Read, Luca Martino, Pablo M. Olmos, David Luengo. Scalable Multi-Output Label Prediction: From Classifier Chains to Classifier Trellises. Pattern Recognition. Vol. 48(6). pp 2096—2109. 2015.

Jesse Read, Luca Martino, Francisco Louzada. Viterbi Classifier Chains for Multi-Dimensional Learning. ArXiv. 2015.

2014

Jesse Read, Antti Puurula, Albert Bifet. Multi-label Classification with Meta Labels. In Proc. of ICDM’14: IEEE International Conference on Data Mining (ICDM 2014). pp 941—946. 2014.

Jesse Read, Jaakko Hollmén. A Deep Interpretation of Classifier Chains. In Proc. of Advances in Intelligent Data Analysis XIII - 13th International Symposium, IDA 2014. pp 251—262. 2014.

Grigorios Tsoumakas, Apostolos Papadopoulos, Weining Qian, Stavros Vologiannidis, Alexander D’yakonov, Antti Puurula, Jesse Read, Jan Svec, Stanislav Semenov. WISE 2014 Challenge: Multi-label Classification of Print Media Articles to Topics. In Proc. of WISE 2014: 15th International Conference on Web Information Systems Engineering. pp 541—548. 2014.

Indrė Žliobaitė, Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes. Evaluation methods and decision theory for classification of streaming data with temporal dependence. Machine Learning. Vol. 98(3). pp 455-482. 2014.

Jesse Read, Albert Bifet. Multi-label Classification. In John Wang (Ed.), Encyclopedia of Business Analytics and Optimization. (pp. 1581—1584). IGI Global. 2014

Albert Bifet, Jesse Read. Data Stream Mining. In John Wang (Ed.), Encyclopedia of Business Analytics and Optimization. (pp. 664—666). IGI Global. 2014

Antti Puurula, Jesse Read, Albert Bifet. Kaggle LSHTC4 Winning Solution. Report on our winning solution to the LSHTC4 Kaggle Competition. 2014.

Luca Martino, Jesse Read, David Luengo. Independent doubly Adaptive Rejection Metropolis Sampling. In Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). pp 7998—8002. 2014.

Jesse Read, Luca Martino, David Luengo. Efficient Monte Carlo Methods for Multi-dimensional Learning with Classifier Chains. Pattern Recognition. Vol. 47(3). pp 1535—1546. 2014.

Jesse Read. Classifier Chains for Multi-target Prediction. MTP 2014: ECML-PKKD 2014 International Workshop on Multi-target Prediction (MTP '14).. 2014.

Jesse Read, Katrin Achutegui, Joaquín Míguez. A Distributed Particle Filter for Nonlinear Tracking in Wireless Sensor Networks. Signal Processing. Vol. 98(May 2014). pp 121—134. 2014.

Jesse Read, Concha Bielza, Pedro Larrãnaga. Multi-Dimensional Classification with Super-Classes. Transactions on Knowledge and Data Engineering. Vol. 26(7). pp 1720—1733. 2014.

2013

Albert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, Geoff Holmes. Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them. In Proc. of ECML-PKDD 2013: 24th European Conference on Machine Learning. pp 465—479. 2013.

Jesse Read, Luca Martino, David Luengo. Efficient Monte Carlo Optimization for Multi-label Classifier Chains. In Proc. of ICASSP 2013: The 38th International Conference on Acoustics, Speech, and Signal Processing. pp 3457—3461. 2013.

Jesse Read, Fernando Perez-Cruz. Deep Learning for Multi-label Classification. ArXiv. 2013.

Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes, Indṙe Žliobaiṫe. CD-MOA: Change Detection Framework for Massive Online Analysis. In Proc. of IDA 2013: 12th International Symposium on Advances in Intelligent Data Analysis. pp 92-103. 2013.

Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes. Efficient Data Stream Classification via Probabilistic Adaptive Windows. In Proc. of SAC 2013: 28th ACM Symposium on Applied Computing. pp 801—806. 2013.

Luca Martino, Jesse Read, David Luengo. Improved Adaptive Rejection Metropolis Sampling. 29th European Meeting of Statisticians (EMS 2013). 2013.

Luca Martino, Jesse Read. On the flexibility of the design of multiple try Metropolis schemes. Computational Statistics. Vol. 28(6). pp 2797—2823. 2013.

2012

Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer. Streaming Multi-label Classification. WAPA 2011: Workshop on Applications of Pattern Analysis. 2012.

Luca Martino, Victor Pascual Del Olmo, Jesse Read. A multi-point Metropolis scheme with generic weight functions. Statistics and Probability Letters. Vol. 82(7). pp 1445-1453. 2012.

Jesse Read, Albert Bifet, Bernhard Pfahringer, Geoff Holmes. Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data. In Proc. of IDA 2012: 11th International Symposium on Advances in Intelligent Data Analysis. pp 313-323. 2012.

Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read. Stream Data Mining Using the MOA Framework. In Proc. of DASFAA '12: 17th International Conference on Database Systems for Advanced Applications. pp 309-313. 2012.

Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer. Scalable and efficient multi-label classification for evolving data streams. Machine Learning. Vol. 88(1-2). pp 243-272. 2012.

2011

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 '11: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 2011.

Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank. Classifier Chains for Multi-label Classification. Machine Learning. Vol. 85(3). pp 333-359. 2011.

2010

Albert Bifet, Jesse Read, Geoff Holmes, Bernhard Pfahringer. Efficient Multi-label Classification for Evolving Data Streams. Technical Report 2010/04. 2010.

Jesse Read. Scalable Multi-label Classification. PhD Thesis. University of Waikato, Hamilton, New Zealand. 2010.

2009

Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank. Classifier Chains for Multi-label Classification. In Proc. of ECML 2009: 20th European Conference on Machine Learning. pp 254—269. 2009.

Jesse Read, Bernhard Pfahringer, Geoff Holmes. Generating Synthetic Multi-label Data Streams. MLD 2009: 1st ECML/PKDD 2009 Workshop on Learning from Multi-Label Data. 2009.

2008

Jesse Read, Bernhard Pfahringer, Geoff Holmes. Multi-label Classification Using Ensembles of Pruned Sets. In Proc. of ICDM 2008: Eighth IEEE International Conference on Data Mining. pp 995-1000. 2008.

Jesse Read. A Pruned Problem Transformation Method for Multi-label classification. In Proc. of NZCSRS 08: 2008 New Zealand Computer Science Research Student Conference. pp 143—150. 2008.

2007

Daniel Kuen Seong Su, Victoria Siew Yen Yee, Jesse Read. Exploring Text-based and Graphical-based Usable Interfaces for Mobile Chat Systems. eMinds International Journal on Human-Computer Interaction. Vol. 1(3). pp 37-53. 2007.

2005

Jesse Read. Filtering Spam with Machine Learning. Honours Thesis. University of Waikato, Hamilton, New Zealand. 2005.