Jesse Read
TitleCited byYear
Classifier chains for multi-label classification
J Read, B Pfahringer, G Holmes, E Frank
Machine learning 85 (3), 333, 2011
11182011
Classifier chains for multi-label classification
J Read, B Pfahringer, G Holmes, E Frank
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2009
5832009
Multi-label classification using ensembles of pruned sets
J Read, B Pfahringer, G Holmes
8th IEEE international conference on data mining, 995-1000, 2008
3442008
A pruned problem transformation method for multi-label classification
J Read
Proc. 2008 New Zealand Computer Science Research Student Conference (NZCSRS …, 2008
1982008
Meka: a multi-label/multi-target extension to weka
J Read, P Reutemann, B Pfahringer, G Holmes
The Journal of Machine Learning Research 17 (1), 667-671, 2016
1582016
Scalable and efficient multi-label classification for evolving data streams
J Read, A Bifet, G Holmes, B Pfahringer
Machine Learning 88 (1-2), 243-272, 2012
1022012
Adaptive random forests for evolving data stream classification
HM Gomes, A Bifet, J Read, JP Barddal, F Enembreck, B Pfharinger, ...
Machine Learning 106 (9-10), 1469-1495, 2017
982017
Efficient online evaluation of big data stream classifiers
A Bifet, G de Francisci Morales, J Read, G Holmes, B Pfahringer
Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015
932015
Scalable multi-label classification
J Read
University of Waikato, 2010
822010
Batch-incremental versus instance-incremental learning in dynamic and evolving data
J Read, A Bifet, B Pfahringer, G Holmes
International Symposium on Intelligent Data Analysis, 313-323, 2012
802012
Efficient monte carlo methods for multi-dimensional learning with classifier chains
J Read, L Martino, D Luengo
Pattern Recognition 47 (3), 1535-1546, 2014
762014
Evaluation methods and decision theory for classification of streaming data with temporal dependence
I Žliobaitė, A Bifet, J Read, B Pfahringer, G Holmes
Machine Learning 98 (3), 455-482, 2015
752015
Cooperative parallel particle filters for online model selection and applications to urban mobility
L Martino, J Read, V Elvira, F Louzada
Digital Signal Processing 60, 172-185, 2017
742017
Pitfalls in benchmarking data stream classification and how to avoid them
A Bifet, J Read, I Žliobaitė, B Pfahringer, G Holmes
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2013
682013
Independent doubly adaptive rejection Metropolis sampling within Gibbs sampling
L Martino, J Read, D Luengo
IEEE Transactions on Signal Processing 63 (12), 3123-3138, 2015
552015
Efficient data stream classification via probabilistic adaptive windows
A Bifet, B Pfahringer, J Read, G Holmes
Proceedings of the 28th annual ACM symposium on applied computing, 801-806, 2013
532013
Scalable multi-output label prediction: From classifier chains to classifier trellises
J Read, L Martino, PM Olmos, D Luengo
Pattern Recognition 48 (6), 2096-2109, 2015
522015
A distributed particle filter for nonlinear tracking in wireless sensor networks
J Read, K Achutegui, J Míguez
Signal Processing 98, 121-134, 2014
522014
On the flexibility of the design of multiple try Metropolis schemes
L Martino, J Read
Computational Statistics 28 (6), 2797-2823, 2013
472013
MOA: a real-time analytics open source framework
A Bifet, G Holmes, B Pfahringer, J Read, P Kranen, H Kremer, T Jansen, ...
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
472011
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