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

Publications

Journals

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

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 & Software. Vol. 127 (May). pp 195—204. 2017.

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.

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.

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

Indre Zliobaite, Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes. Evaluation methods and decision theory for classification of streaming data with temporal dependence. Machine Learning Journal. 98(3). pp 455-482. 2015.

Jesse Read, Katrin Achutegui, Joaquin Miguez. A distributed particle filter for nonlinear tracking in wireless sensor networks. Elsevier Signal Processing. Vol. 98(2014), pp 121-134. 2014.

Jesse Read, Concha Bielza, Pedro Larranaga. Multi-Dimensional Classification with Super-Classes. IEEE Transactions on Knowledge and Data Engineering. Vol. 26(7). 2014.

Jesse Read, Luca Martino, David Luengo. Efficient Monte Carlo Methods for Multi-Dimensional Learning with Classifier Chains. Pattern Recognition. Elsevier. Vol. 47(3). 2014.

Luca Martino, Jesse Read. On the Flexibility of the Design of Multiple Try Metropolis Schemes. Computational Statistics. DOI 10.1007/s00180-013-0429-2, 2013.

Luca Martino, Victor Pascual del Olmo, Jesse Read. A Multi-point Metropolis Scheme with Generic Weight Functions. Statistics and Probability Letters. Vol. 82(7). April 2012.

Jesse Read, Albert Bifet, Bernhard Pfahringer, Geoff Holmes. Scalable and Efficient Multi-label Classification for Evolving Data Streams. Machine Learning Journal. Springer. Vol. 88(Numbers 1-2), pp 243-272. (January 2012)

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

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

Conference Proceedings

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. 2016.

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. Sydney, Australia, 2015

Jesse Read, Fernando Perez-Cruz, Albert Bifet. Deep Learning in Partially-Labeled Data Streams. In Proc. of The 30th ACM Symposium on Applied Computing (SAC 2015). Salamanca, Spain. 2015.

Jesse Read, Antti Puurula, Albert Bifet. Multi-label Classification with Meta Labels[slides]. In Proc. of IEEE International Conference on Data Mining (ICDM 2014). pp 941-946. December 2014.

Jesse Read, Jaakko Hollmen. A Deep Interpretation of Classifier Chains [slides]. In Proc of The Thirteenth International Symposium on Intelligent Data Analysis (IDA 2014). LNCS 8819, pp 251-262. Springer. Leuven, Belgium. 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 15th International Conference on Web Information Systems Engineering (WISE 2014), LNCS 8787 Part II, pp 541-548. Springer. October 12-14, 2014. See also: [slides of our team’s solution (Antti Puurula, Jesse Read)]

Luca Martino, Jesse Read, David Luengo. Independent doubly adaptive rejection Metropolis sampling. In Proc. of the IEEE 39th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014).

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

Albert Bifet, Jesse Read, Bernhard Pfahringer, and Geoff Holmes, Indre Zliobaite. CD-MOA: Change Detection Framework for Massive Online Analysis. In Proc. of The 12th International Symposium on Intelligent Data Analysis (IDA 2013). 2013.

Albert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, and Geoff Holmes. Pitfalls in benchmarking data stream classification and how to avoid them. In Proc. of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2013). 2013.

Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes. Efficient Data Stream Classification via Probabilistic Adaptive Windows. In Proc. of The 28th ACM Symposium on Applied Computing (SAC 2013). Coimbra, Portugal 2013.

Jesse Read, Albert Bifet, Bernhard Pfahringer, Geoff Holmes. Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data [slides]. In Proc. of The Eleventh International Symposium on Intelligent Data Analysis (IDA 2012). Helsinki, Finland. October 2012

Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank. Classifier Chains for Multi-label Classification. In Proc. of 20th European Conference on Machine Learning (ECML 2009). Bled, Slovenia, September 2009. [slides] [poster]

Jesse Read, Bernhard Pfahringer, Geoff Holmes. Multi-label Classification using Ensembles of Pruned Sets. Proc. of IEEE International Conference on Data Mining (ICDM 2008). Pisa, Italy, December 2008. (long version) [slides]

Jesse Read. A Pruned Problem Transformation Method for Multi-label Classification. In Proc. of the NZ Computer Science Research Student Conference. Christchurch, New Zealand (2008). [slides]

Workshops and Demos

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, 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. Helsinki, Finland. 2015.

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

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

Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer. Streaming Multi-label Classification [slides] [video] Workshop on Applications of Pattern Analysis (WAPA). Castro-Urdiales, Spain. October 2011

Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read, 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. September, 2011

Jesse Read, Bernhard Pfahringer, Geoff Holmes. Generating Synthetic Multi-label Data Streams. In Proc. of ECML/PKKD 2009 Workshop on Learning from Multi-label Data (MLD’09). Bled, Slovenia, September 2009. [poster]

Technical Reports

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

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

Theses

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

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

Book Chapters

Albert Bifet, Jesse Read. Data Stream Mining. In Wang, John. Editor (Ed.), Encyclopedia of Business Analytics and Optimization (5 Volumes) Chapter 61 (pp. 664 - 666). IGI Global. (2014)

Jesse Read, Albert Bifet. Multi-label Classification. In Wang, John. Editor (Ed.), Encyclopedia of Business Analytics and Optimization (5 Volumes) Chapter 142 (pp. 1581 - 1584). IGI Global. (2014)

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Citations

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