Unsupervised visual domain adaptation using subspace alignment B Fernando, A Habrard, M Sebban, T Tuytelaars Proceedings of the IEEE international conference on computer vision, 2960-2967, 2013 | 1534 | 2013 |
A survey on metric learning for feature vectors and structured data A Bellet, A Habrard, M Sebban arXiv preprint arXiv:1306.6709, 2013 | 832 | 2013 |
Metric learning A Bellet, A Habrard, M Sebban Synthesis lectures on artificial intelligence and machine learning 9 (1), 1-151, 2015 | 275 | 2015 |
A hybrid filter/wrapper approach of feature selection using information theory M Sebban, R Nock Pattern recognition 35 (4), 835-846, 2002 | 198 | 2002 |
Theoretical analysis of domain adaptation with optimal transport I Redko, A Habrard, M Sebban Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 190 | 2017 |
Advances in domain adaptation theory I Redko, E Morvant, A Habrard, M Sebban, Y Bennani Elsevier, 2019 | 159 | 2019 |
Landmarks-based kernelized subspace alignment for unsupervised domain adaptation R Aljundi, R Emonet, D Muselet, M Sebban Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 151 | 2015 |
A survey on domain adaptation theory: learning bounds and theoretical guarantees I Redko, E Morvant, A Habrard, M Sebban, Y Bennani arXiv preprint arXiv:2004.11829, 2020 | 147 | 2020 |
A data-mining approach to spacer oligonucleotide typing of Mycobacterium tuberculosis M Sebban, I Mokrousov, N Rastogi, C Sola Bioinformatics 18 (2), 235-243, 2002 | 138 | 2002 |
Discriminative feature fusion for image classification B Fernando, E Fromont, D Muselet, M Sebban 2012 IEEE Conference on Computer Vision and Pattern Recognition, 3434-3441, 2012 | 122 | 2012 |
Learning stochastic edit distance: Application in handwritten character recognition J Oncina, M Sebban Pattern recognition 39 (9), 1575-1587, 2006 | 91 | 2006 |
Subspace alignment for domain adaptation B Fernando, A Habrard, M Sebban, T Tuytelaars arXiv preprint arXiv:1409.5241, 2014 | 77 | 2014 |
Similarity learning for provably accurate sparse linear classification A Bellet, A Habrard, M Sebban arXiv preprint arXiv:1206.6476, 2012 | 75 | 2012 |
Efficient top rank optimization with gradient boosting for supervised anomaly detection J Frery, A Habrard, M Sebban, O Caelen, L He-Guelton Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 65 | 2017 |
Supervised learning of Gaussian mixture models for visual vocabulary generation B Fernando, E Fromont, D Muselet, M Sebban Pattern Recognition 45 (2), 897-907, 2012 | 63 | 2012 |
Good edit similarity learning by loss minimization A Bellet, A Habrard, M Sebban Machine Learning 89, 5-35, 2012 | 58 | 2012 |
Metric learning from imbalanced data with generalization guarantees L Gautheron, A Habrard, E Morvant, M Sebban Pattern Recognition Letters 133, 298-304, 2020 | 57* | 2020 |
Platelet components associated with adverse reactions: predictive value of mitochondrial DNA relative to biological response modifiers F Cognasse, C Aloui, K Anh Nguyen, H Hamzeh‐Cognasse, J Fagan, ... Transfusion 56 (2), 497-504, 2016 | 56 | 2016 |
Learning probabilistic models of tree edit distance M Bernard, L Boyer, A Habrard, M Sebban Pattern Recognition 41 (8), 2611-2629, 2008 | 54 | 2008 |
A computerized prediction model of hazardous inflammatory platelet transfusion outcomes KA Nguyen, H Hamzeh-Cognasse, M Sebban, E Fromont, P Chavarin, ... PLoS One 9 (5), e97082, 2014 | 53 | 2014 |