Seguir
Emilie Morvant
Emilie Morvant
Assistant Professor, University of Saint-Etienne (France), Hubert Curien Laboratory
Dirección de correo verificada de univ-st-etienne.fr - Página principal
Título
Citado por
Citado por
Año
Advances in domain adaptation theory
I Redko, E Morvant, A Habrard, M Sebban, Y Bennani
Elsevier, 2019
331*2019
Majority vote of diverse classifiers for late fusion
E Morvant, A Habrard, S Ayache
Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2014
1602014
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
1492013
A new PAC-Bayesian perspective on domain adaptation
P Germain, A Habrard, F Laviolette, E Morvant
International conference on machine learning, 859-868, 2016
852016
Metric learning from imbalanced data with generalization guarantees
L Gautheron, A Habrard, E Morvant, M Sebban
Pattern Recognition Letters 133, 298-304, 2020
352020
PAC-Bayesian generalization bound on confusion matrix for multi-class classification
E Morvant, S Koço, L Ralaivola
arXiv preprint arXiv:1202.6228, 2012
342012
A pac-bayes analysis of adversarial robustness
P Viallard, EG VIDOT, A Habrard, E Morvant
Advances in Neural Information Processing Systems 34, 14421-14433, 2021
332021
PAC-Bayes and domain adaptation
P Germain, A Habrard, F Laviolette, E Morvant
Neurocomputing 379, 379-397, 2020
332020
Parsimonious unsupervised and semi-supervised domain adaptation with good similarity functions
E Morvant, A Habrard, S Ayache
Knowledge and Information Systems 33, 309-349, 2012
322012
Metric learning from imbalanced data
L Gautheron, A Habrard, E Morvant, M Sebban
2019 IEEE 31st International Conference on Tools with Artificial …, 2019
282019
Pac-bayesian analysis for a two-step hierarchical multiview learning approach
A Goyal, E Morvant, P Germain, MR Amini
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017
262017
A general framework for the practical disintegration of PAC-Bayesian bounds
P Viallard, P Germain, A Habrard, E Morvant
Machine Learning 113 (2), 519-604, 2024
25*2024
Learning stochastic majority votes by minimizing a PAC-Bayes generalization bound
V Zantedeschi, P Viallard, E Morvant, R Emonet, A Habrard, P Germain, ...
Advances in Neural Information Processing Systems 34, 455-467, 2021
192021
Risk upper bounds for general ensemble methods with an application to multiclass classification
F Laviolette, E Morvant, L Ralaivola, JF Roy
Neurocomputing 219, 15-25, 2017
192017
Domain adaptation of weighted majority votes via perturbed variation-based self-labeling
E Morvant
Pattern Recognition Letters, 2014
182014
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
162019
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
142013
Self-bounding majority vote learning algorithms by the direct minimization of a tight PAC-Bayesian C-bound
P Viallard, P Germain, A Habrard, E Morvant
Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021
102021
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
102015
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
102011
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20