Marc Sebban
Marc Sebban
Professor of Computer Science, Jean Monnet University
Verified email at
Cited by
Cited by
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
A survey on metric learning for feature vectors and structured data
A Bellet, A Habrard, M Sebban
arXiv preprint arXiv:1306.6709, 2013
A hybrid filter/wrapper approach of feature selection using information theory
M Sebban, R Nock
Pattern recognition 35 (4), 835-846, 2002
Metric learning
A Bellet, A Habrard, M Sebban
Synthesis Lectures on Artificial Intelligence and Machine Learning 9 (1), 1-151, 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
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
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
Learning stochastic edit distance: Application in handwritten character recognition
J Oncina, M Sebban
Pattern recognition 39 (9), 1575-1587, 2006
Similarity learning for provably accurate sparse linear classification
A Bellet, A Habrard, M Sebban
arXiv preprint arXiv:1206.6476, 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
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
Subspace alignment for domain adaptation
B Fernando, A Habrard, M Sebban, T Tuytelaars
arXiv preprint arXiv:1409.5241, 2014
Learning probabilistic models of tree edit distance
M Bernard, L Boyer, A Habrard, M Sebban
Pattern Recognition 41 (8), 2611-2629, 2008
Good edit similarity learning by loss minimization
A Bellet, A Habrard, M Sebban
Machine Learning 89 (1-2), 5-35, 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
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
Advances in domain adaptation theory
I Redko, E Morvant, A Habrard, M Sebban, Y Bennani
Elsevier, 2019
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
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
Melody recognition with learned edit distances
A Habrard, JM Inesta, D Rizo, M Sebban
Joint IAPR International Workshops on Statistical Techniques in Pattern …, 2008
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