| 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 | 988 | 2013 |
| A survey on metric learning for feature vectors and structured data A Bellet, A Habrard, M Sebban arXiv preprint arXiv:1306.6709, 2013 | 636 | 2013 |
| A hybrid filter/wrapper approach of feature selection using information theory M Sebban, R Nock Pattern recognition 35 (4), 835-846, 2002 | 164 | 2002 |
| Metric learning A Bellet, A Habrard, M Sebban Synthesis Lectures on Artificial Intelligence and Machine Learning 9 (1), 1-151, 2015 | 150 | 2015 |
| 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 | 136 | 2002 |
| 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 | 117 | 2015 |
| 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 | 99 | 2012 |
| Learning stochastic edit distance: Application in handwritten character recognition J Oncina, M Sebban Pattern recognition 39 (9), 1575-1587, 2006 | 86 | 2006 |
| Similarity learning for provably accurate sparse linear classification A Bellet, A Habrard, M Sebban arXiv preprint arXiv:1206.6476, 2012 | 66 | 2012 |
| 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 | 59 | 2012 |
| Theoretical analysis of domain adaptation with optimal transport I Redko, A Habrard, M Sebban Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 56 | 2017 |
| Learning probabilistic models of tree edit distance M Bernard, L Boyer, A Habrard, M Sebban Pattern Recognition 41 (8), 2611-2629, 2008 | 53 | 2008 |
| Subspace alignment for domain adaptation B Fernando, A Habrard, M Sebban, T Tuytelaars arXiv preprint arXiv:1409.5241, 2014 | 48 | 2014 |
| Good edit similarity learning by loss minimization A Bellet, A Habrard, M Sebban Machine Learning 89 (1-2), 5-35, 2012 | 46 | 2012 |
| 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 | 43 | 2014 |
| Stopping criterion for boosting-based data reduction techniques: From binary to multiclass problem. M Sebban, R Nock, S Lallich J. Mach. Learn. Res. 3, 863-885, 2002 | 40 | 2002 |
| 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 | 37 | 2016 |
| A simple locally adaptive nearest neighbor rule with application to pollution forecasting R Nock, M Sebban, D Bernard International Journal of Pattern Recognition and Artificial Intelligence 17 …, 2003 | 35 | 2003 |
| Melody recognition with learned edit distances A Habrard, JM Inesta, D Rizo, M Sebban Joint IAPR International Workshops on Statistical Techniques in Pattern …, 2008 | 34 | 2008 |
| Efficient top rank optimization with gradient boosting for supervised anomaly detection J Frery, A Habrard, M Sebban, O Caelen, L He-Guelton Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 28 | 2017 |
Amaury HabrardProfessor of Computer Science, University Jean Monnet of Saint-Etienne (France)univ-st-etienne.fr의 이메일 확인됨
