Emilie Morvant

53 papers A* 5A 2B 2C 1Journal 32Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	PAC-Bayesian Generalization Guarantees for Fairness on Stochastic and Deterministic Classifiers. CoRR Julien Bastian, Benjamin Leblanc, Pascal Germain, Amaury Habrard, Christine Largeron, Guillaume Metzler, Emilie Morvant, Paul Viallard
2025	—	`book`	Avancées en théorie PAC-Bayésienne : de bornes en généralisation à des algorithmes d'apprentissage supervisé et de transfert. (Advances in PAC-Bayesian theory from generalization bounds to supervised and transfer learning algorithms). Emilie Morvant
2025	J	`jnl`	PAC-Bayesian Bounds on Constrained f-Entropic Risk Measures. CoRR Hind Atbir, Farah Cherfaoui, Guillaume Metzler, Emilie Morvant, Paul Viallard
2024	—	`conf`	A Theoretically Grounded Extension of Universal Attacks from the Attacker's Viewpoint. ECML/PKDD (4) Jordan Patracone, Paul Viallard, Emilie Morvant, Gilles Gasso, Amaury Habrard, Stéphane Canu
2024	J	`jnl`	A general framework for the practical disintegration of PAC-Bayesian bounds. Mach. Learn. Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
2024	A	`conf`	Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. AISTATS Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
2024	J	`jnl`	Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. CoRR Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
2021	J	`jnl`	A General Framework for the Derandomization of PAC-Bayesian Bounds. CoRR Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
2021	A*	`conf`	A PAC-Bayes Analysis of Adversarial Robustness. NeurIPS Paul Viallard, Guillaume Vidot, Amaury Habrard, Emilie Morvant
2021	J	`jnl`	A PAC-Bayes Analysis of Adversarial Robustness. CoRR Guillaume Vidot, Paul Viallard, Amaury Habrard, Emilie Morvant
2021	A*	`conf`	Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. NeurIPS Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
2021	J	`jnl`	Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. CoRR Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
2021	J	`jnl`	Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. CoRR Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
2021	—	`conf`	Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. ECML/PKDD (2) Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
2020	J	`jnl`	A survey on domain adaptation theory. CoRR Ievgen Redko, Emilie Morvant, Amaury Habrard, Marc Sebban, Younès Bennani
2020	—	`conf`	Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting. ECML/PKDD (3) Léo Gautheron, Pascal Germain, Amaury Habrard, Guillaume Metzler, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
2020	J	`jnl`	Metric Learning from Imbalanced Data with Generalization Guarantees. Pattern Recognit. Lett. Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban
2020	J	`jnl`	PAC-Bayes and domain adaptation. Neurocomputing Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2019	J	`jnl`	Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting. CoRR Léo Gautheron, Pascal Germain, Amaury Habrard, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
2019	B	`conf`	Metric Learning from Imbalanced Data. ICTAI Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban
2019	J	`jnl`	Metric Learning from Imbalanced Data. CoRR Léo Gautheron, Emilie Morvant, Amaury Habrard, Marc Sebban
2019	J	`jnl`	Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters. Neurocomputing Anil Goyal, Emilie Morvant, Pascal Germain, Massih-Reza Amini
2019	A	`conf`	Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior. AISTATS Gaël Letarte, Emilie Morvant, Pascal Germain
2018	J	`jnl`	Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters. CoRR Anil Goyal, Emilie Morvant, Pascal Germain, Massih-Reza Amini
2018	B	`conf`	Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization. IDA Anil Goyal, Emilie Morvant, Massih-Reza Amini
2018	J	`jnl`	Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization. CoRR Anil Goyal, Emilie Morvant, Massih-Reza Amini
2018	J	`jnl`	Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior. CoRR Gaël Letarte, Emilie Morvant, Pascal Germain
2017	—	`conf`	PAC-Bayesian Analysis for a Two-Step Hierarchical Multiview Learning Approach. ECML/PKDD (2) Anil Goyal, Emilie Morvant, Pascal Germain, Massih-Reza Amini
2017	J	`jnl`	Risk upper bounds for general ensemble methods with an application to multiclass classification. Neurocomputing François Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy
2016	A*	`conf`	A New PAC-Bayesian Perspective on Domain Adaptation. ICML Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2015	J	`jnl`	A New PAC-Bayesian Perspective on Domain Adaptation. CoRR Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2015	J	`jnl`	An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context. CoRR Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2015	J	`jnl`	Domain adaptation of weighted majority votes via perturbed variation-based self-labeling. Pattern Recognit. Lett. Emilie Morvant
2015	J	`jnl`	On Generalizing the C-Bound to the Multiclass and Multi-label Settings. CoRR François Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy
2015	J	`jnl`	PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers. CoRR Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2014	J	`jnl`	Domain adaptation of weighted majority votes via perturbed variation-based self-labeling. CoRR Emilie Morvant
2014	J	`jnl`	Learning a priori constrained weighted majority votes. Mach. Learn. Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban
2014	—	`conf`	Majority Vote of Diverse Classifiers for Late Fusion. S+SSPR Emilie Morvant, Amaury Habrard, Stéphane Ayache
2014	J	`jnl`	Majority Vote of Diverse Classifiers for Late Fusion. CoRR Emilie Morvant, Amaury Habrard, Stéphane Ayache
2014	—	`conf`	Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks. NIPS Mario Marchand, Hongyu Su, Emilie Morvant, Juho Rousu, John Shawe-Taylor
2014	J	`jnl`	Proceedings of The 38th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM), 2014. CoRR Vladimir Kolmogorov, Christoph H. Lampert, Emilie Morvant, Rustem Takhanov
2013	—	`conf`	A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers. ICML (3) Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2013	—	`—`	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). Emilie Morvant
2013	J	`jnl`	Domain Adaptation of Majority Votes via Perturbed Variation-based Label Transfer. CoRR Emilie Morvant
2013	C	`conf`	The Multi-Task Learning View of Multimodal Data. ACML Hachem Kadri, Stéphane Ayache, Cécile Capponi, Sokol Koço, François-Xavier Dupé, Emilie Morvant
2012	J	`jnl`	PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification CoRR Emilie Morvant, Sokol Koço, Liva Ralaivola
2012	A*	`conf`	PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification. ICML Emilie Morvant, Sokol Koço, Liva Ralaivola
2012	J	`jnl`	PAC-Bayesian Learning and Domain Adaptation CoRR Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2012	J	`jnl`	PAC-Bayesian Majority Vote for Late Classifier Fusion CoRR Emilie Morvant, Amaury Habrard, Stéphane Ayache
2012	J	`jnl`	Parsimonious unsupervised and semi-supervised domain adaptation with good similarity functions. Knowl. Inf. Syst. Emilie Morvant, Amaury Habrard, Stéphane Ayache
2011	—	`conf`	On the Usefulness of Similarity Based Projection Spaces for Transfer Learning. SIMBAD Emilie Morvant, Amaury Habrard, Stéphane Ayache
2011	A*	`conf`	Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions. ICDM Emilie Morvant, Amaury Habrard, Stéphane Ayache
2011	—	`conf`	VideoSense at TRECVID 2011: Semantic Indexing from Light Similarity Functions-based Domain Adaptation with Stacking. TRECVID Emilie Morvant, Stéphane Ayache, Amaury Habrard, Miriam Redi, Claudiu Tanase, Bernard Mérialdo, Bahjat Safadi, Franck Thollard, Nadia Derbas, Georges Quénot