Rémi Emonet
13 papers · 2015–2025 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Machine Learning
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Core Methods
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Optimization & Theory · Machine Learning
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Deep Learning
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Mathematics & Optimization
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Optimization
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Optimization & Theory · Deep Learning
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metric learning
(3)
generalization bound
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optimal transport
(3)
wasserstein distance
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pac-bayes theory
(2)
domain adaptation
(2)
pac-bayes bound
(2)
representation learning
(2)
adversarial training
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weakly supervised learning
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text classification
(1)
unsupervised domain adaptation
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distribution matching
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minimax optimization
(1)
similarity learning
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majority vote
(1)
multi-instance learning
(1)
class imbalance
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tensor decomposition
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statistical learning theory
(1)
Papers
A Bregman Proximal Viewpoint on Neural Operators
ICML 2025
Length independent PAC-Bayes bounds for Simple RNNs
AISTATS 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures
AISTATS 2024
Fair Text Classification with Wasserstein Independence
EMNLP 2023
Optimal Tensor Transport
AAAI 2022
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound
NeurIPS 2021
A Swiss Army Knife for Minimax Optimal Transport
ICML 2020
Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data
IJCAI 2020
Metric Learning in Optimal Transport for Domain Adaptation
IJCAI 2020
From Cost-Sensitive Classification to Tight F-measure Bounds
AISTATS 2019
beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data
NeurIPS 2016
Metric Learning as Convex Combinations of Local Models With Generalization Guarantees
CVPR 2016
Landmarks-Based Kernelized Subspace Alignment for Unsupervised Domain Adaptation
CVPR 2015