:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Le, Tam, Malick, Jérôme
Format:	Preprint
Publié:	2024
Sujets:	Optimization and Control Machine Learning
Accès en ligne:	https://arxiv.org/abs/2402.11981
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Unregularized limit of stochastic gradient method for Wasserstein distributionally robust optimization
par: Le, Tam
Publié: (2025)

$\texttt{skwdro}$: a library for Wasserstein distributionally robust machine learning
par: Vincent, Florian, et autres
Publié: (2024)

Inexact subgradient methods for semialgebraic functions
par: Bolte, Jérôme, et autres
Publié: (2024)

Convergence of empirical subgradients for optimal transport-based objectives
par: Le, Tam
Publié: (2026)

A stochastic smoothing framework for nonconvex-nonconcave min-sum-max problems with applications to Wasserstein distributionally robust optimization
par: Liu, Wei, et autres
Publié: (2025)

Data-driven robust Markov decision processes on Borel spaces: performance guarantees via an axiomatic approach
par: Ramani, Sivaramakrishnan
Publié: (2026)

RGNMR: A Gauss-Newton method for robust matrix completion with theoretical guarantees
par: Laufer, Eilon Vaknin, et autres
Publié: (2025)

Proximal basin hopping: global optimization with guarantees
par: Lauga, Guillaume, et autres
Publié: (2026)

Automatic nonlinear MPC approximation with closed-loop guarantees
par: Tokmak, Abdullah, et autres
Publié: (2023)

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows
par: Bonet, Clément, et autres
Publié: (2025)

Tight Robustness Certificates and Wasserstein Distributional Attacks for Deep Neural Networks
par: Le, Bach C., et autres
Publié: (2025)

Finite-sample guarantees for data-driven forward-backward operator methods
par: Fabiani, Filippo, et autres
Publié: (2025)

Learning to accelerate Krasnosel'skii-Mann fixed-point iterations with guarantees
par: Martin, Andrea, et autres
Publié: (2026)

Learning to optimize with guarantees: a complete characterization of linearly convergent algorithms
par: Martin, Andrea, et autres
Publié: (2025)

A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees
par: Li, Shuyao, et autres
Publié: (2023)

A robust and adaptive MPC formulation for Gaussian process models
par: Dubied, Mathieu, et autres
Publié: (2025)

A universal policy wrapper with guarantees
par: Bolychev, Anton, et autres
Publié: (2025)

End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data
par: Chatzikiriakos, Nicolas, et autres
Publié: (2024)

Linear Partial Gromov-Wasserstein Embedding
par: Bai, Yikun, et autres
Publié: (2024)

Wasserstein Distributionally Robust Regret Optimization
par: Fiechtner, Lukas-Benedikt, et autres
Publié: (2025)

Wasserstein Distributionally Robust Online Learning
par: Chen, Guixian, et autres
Publié: (2026)

Semidefinite Relaxations of the Gromov-Wasserstein Distance
par: Chen, Junyu, et autres
Publié: (2023)

Fréchet Regression on the Bures-Wasserstein Manifold
par: Nguyen, Duc Toan, et autres
Publié: (2026)

Sliced Wasserstein Steering between Gaussian Measures
par: Ito, Kaito, et autres
Publié: (2026)

Mirror and Preconditioned Gradient Descent in Wasserstein Space
par: Bonet, Clément, et autres
Publié: (2024)

Non-geodesically-convex optimization in the Wasserstein space
par: Luu, Hoang Phuc Hau, et autres
Publié: (2024)

A note on convergence of Wasserstein policy optimization
par: Šiška, David, et autres
Publié: (2026)

Sliced Inner Product Gromov-Wasserstein Distances
par: Gong, Xiaoyun, et autres
Publié: (2026)

Collaborative Bayesian Optimization via Wasserstein Barycenters
par: Zhan, Donglin, et autres
Publié: (2025)

Wasserstein Distributionally Robust Shallow Convex Neural Networks
par: Pallage, Julien, et autres
Publié: (2024)

A Novel Sliced Fused Gromov-Wasserstein Distance
par: Piening, Moritz, et autres
Publié: (2025)

Wasserstein Barycenter Gaussian Process based Bayesian Optimization
par: Candelieri, Antonio, et autres
Publié: (2025)

It's All in the Mix: Wasserstein Classification and Regression with Mixed Features
par: Belbasi, Reza, et autres
Publié: (2023)

Conditional Sampling via Wasserstein Autoencoders and Triangular Transport
par: Al-Jarrah, Mohammad, et autres
Publié: (2026)

A Computational Framework for Solving Wasserstein Lagrangian Flows
par: Neklyudov, Kirill, et autres
Publié: (2023)

On Generalization and Regularization via Wasserstein Distributionally Robust Optimization
par: Wu, Qinyu, et autres
Publié: (2022)

Random Coordinate Descent on the Wasserstein Space of Probability Measures
par: Xu, Yewei, et autres
Publié: (2026)

Training robust and generalizable quantum models
par: Berberich, Julian, et autres
Publié: (2023)

Slicing Wasserstein Over Wasserstein Via Functional Optimal Transport
par: Piening, Moritz, et autres
Publié: (2025)

Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching
par: Chemseddine, Jannis, et autres
Publié: (2024)