Emilie Morvant

发表

Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks

Juho Rousu, John Shawe-Taylor, Mario Marchand, 2014, NIPS.

Domain Adaptation Problem

Ievgen Redko, Younès Bennani, Marc Sebban, 2019 .

A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers

François Laviolette, Amaury Habrard, Emilie Morvant, 2013, ICML.

Impossibility Theorems for Domain Adaptation

Ievgen Redko, Younès Bennani, Marc Sebban, 2019 .

Domain Adaptation Theory Based on Algorithmic Properties

Ievgen Redko, Younès Bennani, Marc Sebban, 2019 .

PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers pdf

François Laviolette, Amaury Habrard, Emilie Morvant, 2015, ArXiv.

On Generalizing the C-Bound to the Multiclass and Multi-label Settings pdf

François Laviolette, Emilie Morvant, Liva Ralaivola, 2015, ArXiv.

An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context pdf

François Laviolette, Amaury Habrard, Emilie Morvant, 2014, NIPS 2014.

Flexible Domain Adaptation for Multimedia Indexing

Stéphane Ayache, Amaury Habrard, Emilie Morvant, 2011 .

Metric Learning from Imbalanced Data

Marc Sebban, Amaury Habrard, Emilie Morvant, 2019, 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI).

Parsimonious unsupervised and semi-supervised domain adaptation with good similarity functions

Stéphane Ayache, Amaury Habrard, Emilie Morvant, 2012, Knowledge and Information Systems.

Domain adaptation of weighted majority votes via perturbed variation-based self-labeling pdf

Emilie Morvant, Emilie Morvant, 2013, Pattern Recognit. Lett..

The Multi-Task Learning View of Multimodal Data

Stéphane Ayache, Emilie Morvant, Hachem Kadri, 2013, ACML.

Sparse Domain Adaptation in a Good Similarity-Based Projection Space

Stéphane Ayache, Amaury Habrard, Emilie Morvant, 2011, NIPS 2011.

PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification pdf

Emilie Morvant, Liva Ralaivola, Sokol Koço, 2012, ICML.

A survey on domain adaptation theory: learning bounds and theoretical guarantees

Ievgen Redko, Marc Sebban, Amaury Habrard, 2020 .

Advances in Domain Adaptation Theory

Ievgen Redko, Younès Bennani, Marc Sebban, 2019 .

Landmark-based Ensemble Learning with Random Fourier Features and Gradient Boosting

Marc Sebban, Amaury Habrard, Emilie Morvant, 2020 .

Seminal Divergence-based Generalization Bounds

Ievgen Redko, Younès Bennani, Marc Sebban, 2019 .

A survey on domain adaptation theory pdf

Ievgen Redko, Marc Sebban, Amaury Habrard, 2020, ArXiv.

Domain adaptation of weighted majority votes via perturbed variation-based self-labeling pdf

Emilie Morvant, 2015, Pattern Recognit. Lett..

A New PAC-Bayesian View of Domain Adaptation

François Laviolette, Amaury Habrard, Emilie Morvant, 2015, NIPS 2015.

Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting pdf

Marc Sebban, Amaury Habrard, Emilie Morvant, 2019, ArXiv.

State of the Art of Statistical Learning Theory

Ievgen Redko, Younès Bennani, Marc Sebban, 2019 .

Iterative Domain Adaptation Methods

Ievgen Redko, Younès Bennani, Marc Sebban, 2019 .

PAC-Bayesian Analysis for a Two-Step Hierarchical Multiview Learning Approach

Massih-Reza Amini, Emilie Morvant, Anil Goyal, 2016, ECML/PKDD.

On the Usefulness of Similarity Based Projection Spaces for Transfer Learning

Stéphane Ayache, Amaury Habrard, Emilie Morvant, 2011, SIMBAD.

Supplementary Material to A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classiers

Amaury Habrard, Emilie Morvant, Pascal Germain, 2004 .

PAC-Bayesian Theory for Domain Adaptation

Ievgen Redko, Younès Bennani, Marc Sebban, 2019 .

Learning a priori constrained weighted majority votes

Marc Sebban, Amaury Habrard, Emilie Morvant, 2014, Machine Learning.

Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization pdf

Massih-Reza Amini, Emilie Morvant, Anil Goyal, 2018, IDA.

Proceedings of The 38th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM), 2014 pdf

Christoph H. Lampert, Vladimir Kolmogorov, Emilie Morvant, 2014, ArXiv.

Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior pdf

Emilie Morvant, Pascal Germain, Gaël Letarte, 2019, AISTATS.

VideoSense at TRECVID 2011: Semantic Indexing from Light Similarity Functions-based Domain Adaptation with Stacking

Stéphane Ayache, Georges Quénot, Amaury Habrard, 2011, TRECVID.

PAC-Bayesian Learning and Domain Adaptation pdf

François Laviolette, Amaury Habrard, Emilie Morvant, 2012, NIPS 2012.

Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters

Massih-Reza Amini, Emilie Morvant, Anil Goyal, 2019, Neurocomputing.

PAC-Bayesian Majority Vote for Late Classifier Fusion pdf

Stéphane Ayache, Amaury Habrard, Emilie Morvant, 2012, ArXiv.

Metric Learning from Imbalanced Data with Generalization Guarantees

Marc Sebban, Amaury Habrard, Emilie Morvant, 2020, Pattern Recognit. Lett..

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, Emilie Morvant, 2013 .

Majority Vote of Diverse Classifiers for Late Fusion pdf

Stéphane Ayache, Amaury Habrard, Emilie Morvant, 2014, S+SSPR.

PAC-Bayes and domain adaptation

Amaury Habrard, Emilie Morvant, Pascal Germain, 2017, Neurocomputing.

Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions

Stéphane Ayache, Amaury Habrard, Emilie Morvant, 2011, 2011 IEEE 11th International Conference on Data Mining.

Risk upper bounds for general ensemble methods with an application to multiclass classification

François Laviolette, Emilie Morvant, Liva Ralaivola, 2017, Neurocomputing.

A new PAC-Bayesian perspective on domain adaptation

François Laviolette, Amaury Habrard, Emilie Morvant, 2015, ICML 2016.

A General Framework for the Disintegration of PAC-Bayesian Bounds

Amaury Habrard, Emilie Morvant, Pascal Germain, 2021, 2102.08649.

Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound

Amaury Habrard, Emilie Morvant, Pascal Germain, 2021, ECML/PKDD.

A PAC-Bayes Analysis of Adversarial Robustness pdf

Amaury Habrard, Emilie Morvant, Paul Viallard, 2021, ArXiv.

A General Framework for the Derandomization of PAC-Bayesian Bounds pdf

Amaury Habrard, Emilie Morvant, Pascal Germain, 2021, ArXiv.

Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound pdf

Amaury Habrard, Emilie Morvant, Pascal Germain, 2021, NeurIPS.