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Emilie Morvant
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Books and Theses
- 2013
- [b1]Emilie Morvant:
Apprentissage de vote de majorité pour la classification supervisée et l'adaptation de domaine : approches PAC-Bayésiennes et combinaison de similarités. (Learning Majority Vote for Supervised Classification and Domain Adaptation: PAC-Bayesian Approaches and Similarity Combination). Aix-Marseille University, Aix-en-Provence, France, 2013
Journal Articles
- 2024
- [j8]Paul Viallard
, Pascal Germain, Amaury Habrard, Emilie Morvant:
A general framework for the practical disintegration of PAC-Bayesian bounds. Mach. Learn. 113(2): 519-604 (2024) - 2020
- [j7]Pascal Germain
PAC-Bayes and domain adaptation. Neurocomputing 379: 379-397 (2020) - [j6]Léo Gautheron, Amaury Habrard, Emilie Morvant
Metric Learning from Imbalanced Data with Generalization Guarantees. Pattern Recognit. Lett. 133: 298-304 (2020) - 2019
- [j5]Anil Goyal
Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters. Neurocomputing 358: 81-92 (2019) - 2017
- [j4]François Laviolette, Emilie Morvant
Risk upper bounds for general ensemble methods with an application to multiclass classification. Neurocomputing 219: 15-25 (2017) - 2015
- [j3]Emilie Morvant:
Domain adaptation of weighted majority votes via perturbed variation-based self-labeling. Pattern Recognit. Lett. 51: 37-43 (2015) - 2014
- [j2]Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban:
Learning a priori constrained weighted majority votes. Mach. Learn. 97(1-2): 129-154 (2014) - 2012
- [j1]Emilie Morvant, Amaury Habrard, Stéphane Ayache:
Parsimonious unsupervised and semi-supervised domain adaptation with good similarity functions. Knowl. Inf. Syst. 33(2): 309-349 (2012)
Conference and Workshop Papers
- 2024
- [c19]Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi:
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. AISTATS 2024: 3007-3015 - [c18]Jordan Patracone, Paul Viallard, Emilie Morvant, Gilles Gasso, Amaury Habrard, Stéphane Canu:
A Theoretically Grounded Extension of Universal Attacks from the Attacker's Viewpoint. ECML/PKDD (4) 2024: 283-300 - 2021
- [c17]Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj:
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. NeurIPS 2021: 455-467 - [c16]Paul Viallard, Guillaume Vidot, Amaury Habrard, Emilie Morvant:
A PAC-Bayes Analysis of Adversarial Robustness. NeurIPS 2021: 14421-14433 - [c15]Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant:
Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. ECML/PKDD (2) 2021: 167-183 - 2020
- [c14]Léo Gautheron, Pascal Germain
Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting. ECML/PKDD (3) 2020: 141-157 - 2019
- [c13]Gaël Letarte, Emilie Morvant, Pascal Germain:
Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior. AISTATS 2019: 768-776 - [c12]Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban:
Metric Learning from Imbalanced Data. ICTAI 2019: 923-930 - 2018
- [c11]Anil Goyal
Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization. IDA 2018: 124-136 - 2017
- [c10]Anil Goyal
PAC-Bayesian Analysis for a Two-Step Hierarchical Multiview Learning Approach. ECML/PKDD (2) 2017: 205-221 - 2016
- [c9]Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant:
A New PAC-Bayesian Perspective on Domain Adaptation. ICML 2016: 859-868 - 2014
- [c8]Mario Marchand, Hongyu Su, Emilie Morvant, Juho Rousu, John Shawe-Taylor:
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks. NIPS 2014: 873-881 - [c7]Emilie Morvant, Amaury Habrard, Stéphane Ayache:
Majority Vote of Diverse Classifiers for Late Fusion. S+SSPR 2014: 153-162 - 2013
- [c6]Hachem Kadri, Stéphane Ayache, Cécile Capponi, Sokol Koço, François-Xavier Dupé, Emilie Morvant:
The Multi-Task Learning View of Multimodal Data. ACML 2013: 261-276 - [c5]Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant:
A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers. ICML (3) 2013: 738-746 - 2012
- [c4]Emilie Morvant, Sokol Koço, Liva Ralaivola:
PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification. ICML 2012 - 2011
- [c3]Emilie Morvant, Amaury Habrard, Stéphane Ayache:
Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions. ICDM 2011: 457-466 - [c2]Emilie Morvant, Amaury Habrard, Stéphane Ayache:
On the Usefulness of Similarity Based Projection Spaces for Transfer Learning. SIMBAD 2011: 1-16 - [c1]Emilie Morvant, Stéphane Ayache, Amaury Habrard, Miriam Redi, Claudiu Tanase, Bernard Mérialdo, Bahjat Safadi, Franck Thollard, Nadia Derbas, Georges Quénot:
VideoSense at TRECVID 2011: Semantic Indexing from Light Similarity Functions-based Domain Adaptation with Stacking. TRECVID 2011
Informal and Other Publications
- 2024
- [i22]Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi:
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. CoRR abs/2402.13285 (2024) - 2021
- [i21]Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant:
A General Framework for the Derandomization of PAC-Bayesian Bounds. CoRR abs/2102.08649 (2021) - [i20]Guillaume Vidot
A PAC-Bayes Analysis of Adversarial Robustness. CoRR abs/2102.11069 (2021) - [i19]Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant:
Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. CoRR abs/2104.13626 (2021) - [i18]Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj:
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. CoRR abs/2106.12535 (2021) - 2020
- [i17]Ievgen Redko, Emilie Morvant, Amaury Habrard, Marc Sebban, Younès Bennani:
A survey on domain adaptation theory. CoRR abs/2004.11829 (2020) - 2019
- [i16]Léo Gautheron, Pascal Germain, Amaury Habrard, Emilie Morvant, Marc Sebban, Valentina Zantedeschi:
Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting. CoRR abs/1906.06203 (2019) - [i15]Léo Gautheron, Emilie Morvant, Amaury Habrard, Marc Sebban:
Metric Learning from Imbalanced Data. CoRR abs/1909.01651 (2019) - 2018
- [i14]Anil Goyal, Emilie Morvant, Massih-Reza Amini:
Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization. CoRR abs/1805.10212 (2018) - [i13]Anil Goyal, Emilie Morvant, Pascal Germain, Massih-Reza Amini:
Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters. CoRR abs/1808.05784 (2018) - [i12]Gaël Letarte, Emilie Morvant, Pascal Germain:
Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior. CoRR abs/1810.12683 (2018) - 2015
- [i11]François Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy:
On Generalizing the C-Bound to the Multiclass and Multi-label Settings. CoRR abs/1501.03001 (2015) - [i10]Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant:
An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context. CoRR abs/1501.03002 (2015) - [i9]Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant:
PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers. CoRR abs/1503.06944 (2015) - [i8]Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant:
A New PAC-Bayesian Perspective on Domain Adaptation. CoRR abs/1506.04573 (2015) - 2014
- [i7]Vladimir Kolmogorov, Christoph H. Lampert, Emilie Morvant, Rustem Takhanov:
Proceedings of The 38th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM), 2014. CoRR abs/1404.3538 (2014) - [i6]Emilie Morvant, Amaury Habrard, Stéphane Ayache:
Majority Vote of Diverse Classifiers for Late Fusion. CoRR abs/1404.7796 (2014) - [i5]Emilie Morvant:
Domain adaptation of weighted majority votes via perturbed variation-based self-labeling. CoRR abs/1410.0334 (2014) - 2013
- [i4]Emilie Morvant:
Domain Adaptation of Majority Votes via Perturbed Variation-based Label Transfer. CoRR abs/1311.4833 (2013) - 2012
- [i3]Emilie Morvant, Sokol Koço, Liva Ralaivola:
PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification. CoRR abs/1202.6228 (2012) - [i2]Emilie Morvant, Amaury Habrard, Stéphane Ayache:
PAC-Bayesian Majority Vote for Late Classifier Fusion. CoRR abs/1207.1019 (2012) - [i1]Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant:
PAC-Bayesian Learning and Domain Adaptation. CoRR abs/1212.2340 (2012)
Coauthor Index
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