Emilie Morvant
Emilie Morvant
Assistant Professor, University of Saint-Etienne (France), Hubert Curien Laboratory
Verified email at univ-st-etienne.fr - Homepage
Title
Cited by
Cited by
Year
A PAC-Bayesian approach for domain adaptation with specialization to linear classifiers
P Germain, A Habrard, F Laviolette, E Morvant
International conference on machine learning, 738-746, 2013
862013
Majority vote of diverse classifiers for late fusion
E Morvant, A Habrard, S Ayache
Joint IAPR International Workshops on Statistical Techniques in Pattern …, 2014
662014
A new PAC-Bayesian perspective on domain adaptation
P Germain, A Habrard, F Laviolette, E Morvant
International conference on machine learning, 859-868, 2016
392016
Parsimonious unsupervised and semi-supervised domain adaptation with good similarity functions
E Morvant, A Habrard, S Ayache
Knowledge and Information Systems 33 (2), 309-349, 2012
272012
Advances in domain adaptation theory
I Redko, E Morvant, A Habrard, M Sebban, Y Bennani
Elsevier, 2019
262019
PAC-Bayesian generalization bound on confusion matrix for multi-class classification
E Morvant, S Koço, L Ralaivola
arXiv preprint arXiv:1202.6228, 2012
242012
Domain adaptation of weighted majority votes via perturbed variation-based self-labeling
E Morvant
Pattern Recognition Letters, 2014
162014
The multi-task learning view of multimodal data
H Kadri, S Ayache, C Capponi, S Koço, FX Dupé, E Morvant
Asian Conference on Machine Learning, 261-276, 2013
122013
A survey on domain adaptation theory: learning bounds and theoretical guarantees
I Redko, E Morvant, A Habrard, M Sebban, Y Bennani
arXiv e-prints, arXiv: 2004.11829, 2020
10*2020
Sparse domain adaptation in projection spaces based on good similarity functions
E Morvant, A Habrard, S Ayache
2011 IEEE 11th International Conference on Data Mining, 457-466, 2011
92011
Pac-bayesian analysis for a two-step hierarchical multiview learning approach
A Goyal, E Morvant, P Germain, MR Amini
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
82017
Multilabel structured output learning with random spanning trees of max-margin markov networks
M Marchand, H Su, E Morvant, J Rousu, J Shawe-Taylor
Neural Information Processing Systems (NIPS), -, 2014
82014
PAC-Bayes and domain adaptation
P Germain, A Habrard, F Laviolette, E Morvant
Neurocomputing 379, 379-397, 2020
62020
Learning a priori constrained weighted majority votes
A Bellet, A Habrard, E Morvant, M Sebban
Machine learning 97 (1-2), 129-154, 2014
62014
Metric learning from imbalanced data with generalization guarantees
L Gautheron, A Habrard, E Morvant, M Sebban
Pattern Recognition Letters 133, 298-304, 2020
52020
Apprentissage de vote de majorité pour la classification supervisée et l'adaptation de domaine: approches PAC-Bayésiennes et combinaison de similarités
E Morvant
Aix-Marseille Université, 2013
52013
Multiview boosting by controlling the diversity and the accuracy of view-specific voters
A Goyal, E Morvant, P Germain, MR Amini
Neurocomputing 358, 81-92, 2019
42019
PAC-Bayesian theorems for domain adaptation with specialization to linear classifiers
P Germain, A Habrard, F Laviolette, E Morvant
arXiv preprint arXiv:1503.06944, 2015
42015
Pseudo-bayesian learning with kernel fourier transform as prior
G Letarte, E Morvant, P Germain
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
32019
On generalizing the c-bound to the multiclass and multi-label settings
F Laviolette, E Morvant, L Ralaivola, JF Roy
NIPS 2014 Workshop on Representation and Learning Methods for Complex Outputs, 2014
32014
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