Stochastic Optimization in Semi-Discrete Optimal Transport: Convergence Analysis and Minimax Rate
Fuente:
arXiv
Saved in:
| Main Authors: | Genans, Ferdinand, Godichon-Baggioni, Antoine, Vialard, François-Xavier, Wintenberger, Olivier |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Semi-Discrete Optimal Transport: Nearly Minimax Estimation With Stochastic Gradient Descent and Adaptive Entropic Regularization
by: Genans, Ferdinand, et al.
Published: (2024)
by: Genans, Ferdinand, et al.
Published: (2024)
Decreasing Entropic Regularization Averaged Gradient for Semi-Discrete Optimal Transport
by: Genans, Ferdinand, et al.
Published: (2025)
by: Genans, Ferdinand, et al.
Published: (2025)
Geometry-Aware Optimal Transport: Fast Intrinsic Dimension and Wasserstein Distance Estimation
by: Genans, Ferdinand, et al.
Published: (2026)
by: Genans, Ferdinand, et al.
Published: (2026)
Convergence in quadratic mean of averaged stochastic gradient algorithms without strong convexity nor bounded gradient
by: Godichon-Baggioni, Antoine
Published: (2021)
by: Godichon-Baggioni, Antoine
Published: (2021)
A Full Adagrad algorithm with O(Nd) operations
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
Online and Offline Robust Multivariate Linear Regression
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
On Adaptive Stochastic Optimization for Streaming Data: A Newton's Method with O(dN) Operations
by: Godichon-Baggioni, Antoine, et al.
Published: (2023)
by: Godichon-Baggioni, Antoine, et al.
Published: (2023)
Minimax-optimal and Locally-adaptive Online Nonparametric Regression
by: Liautaud, Paul, et al.
Published: (2024)
by: Liautaud, Paul, et al.
Published: (2024)
Minimax Adaptive Online Nonparametric Regression over Besov Spaces
by: Liautaud, Paul, et al.
Published: (2025)
by: Liautaud, Paul, et al.
Published: (2025)
High-Probability Minimax Adaptive Estimation in Besov Spaces via Online-to-Batch
by: Liautaud, Paul, et al.
Published: (2026)
by: Liautaud, Paul, et al.
Published: (2026)
A penalized criterion for selecting the number of clusters for K-medians
by: Godichon-Baggioni, Antoine, et al.
Published: (2022)
by: Godichon-Baggioni, Antoine, et al.
Published: (2022)
Fast and Large-Scale Unbalanced Optimal Transport via its Semi-Dual and Adaptive Gradient Methods
by: Genans, Ferdinand
Published: (2026)
by: Genans, Ferdinand
Published: (2026)
Convergence of Multi-Level Markov Chain Monte Carlo Adaptive Stochastic Gradient Algorithms
by: Godichon-Baggioni, Antoine, et al.
Published: (2026)
by: Godichon-Baggioni, Antoine, et al.
Published: (2026)
Minimax Rate-Optimal Algorithms for High-Dimensional Stochastic Linear Bandits
by: Liu, Jingyu, et al.
Published: (2025)
by: Liu, Jingyu, et al.
Published: (2025)
Complexity reduction in online stochastic Newton methods with potential O(N d) total cost
by: Godichon-Baggioni, Antoine, et al.
Published: (2026)
by: Godichon-Baggioni, Antoine, et al.
Published: (2026)
Minimax Optimal Estimation of Transport-Growth Pairs in Unbalanced Optimal Transport
by: Ponnoprat, Donlapark, et al.
Published: (2026)
by: Ponnoprat, Donlapark, et al.
Published: (2026)
Minimax Rates of Estimation for Optimal Transport Map between Infinite-Dimensional Spaces
by: Ponnoprat, Donlapark, et al.
Published: (2025)
by: Ponnoprat, Donlapark, et al.
Published: (2025)
Theoretical Convergence Guarantees for Variational Autoencoders
by: Surendran, Sobihan, et al.
Published: (2024)
by: Surendran, Sobihan, et al.
Published: (2024)
Estimation of Stochastic Optimal Transport Maps
by: Nietert, Sloan, et al.
Published: (2025)
by: Nietert, Sloan, et al.
Published: (2025)
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation
by: Surendran, Sobihan, et al.
Published: (2024)
by: Surendran, Sobihan, et al.
Published: (2024)
Online Covariance Estimation in Averaged SGD: Improved Batch-Mean Rates and Minimax Optimality via Trajectory Regression
by: Ni, Yijin, et al.
Published: (2026)
by: Ni, Yijin, et al.
Published: (2026)
Gradient Descent with Projection Finds Over-Parameterized Neural Networks for Learning Low-Degree Polynomials with Nearly Minimax Optimal Rate
by: Yang, Yingzhen, et al.
Published: (2026)
by: Yang, Yingzhen, et al.
Published: (2026)
On Instability of Minimax Optimal Optimism-Based Bandit Algorithms
by: Praharaj, Samya, et al.
Published: (2025)
by: Praharaj, Samya, et al.
Published: (2025)
Minimax Optimality of the Probability Flow ODE for Diffusion Models
by: Cai, Changxiao, et al.
Published: (2025)
by: Cai, Changxiao, et al.
Published: (2025)
Optimal Convergence Analysis of DDPM for General Distributions
by: Jiao, Yuchen, et al.
Published: (2025)
by: Jiao, Yuchen, et al.
Published: (2025)
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking
by: Rioux, Gabriel, et al.
Published: (2024)
by: Rioux, Gabriel, et al.
Published: (2024)
Optimal Recovery Meets Minimax Estimation
by: DeVore, Ronald, et al.
Published: (2025)
by: DeVore, Ronald, et al.
Published: (2025)
Minimax Rates for Learning Pairwise Interactions in Attention-Style Models
by: Zucker, Shai, et al.
Published: (2025)
by: Zucker, Shai, et al.
Published: (2025)
Minimax-Optimal Two-Sample Test with Sliced Wasserstein
by: Tran, Binh Thuan, et al.
Published: (2025)
by: Tran, Binh Thuan, et al.
Published: (2025)
The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli
by: Cohen, Doron, et al.
Published: (2024)
by: Cohen, Doron, et al.
Published: (2024)
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
by: Li, Gen, et al.
Published: (2021)
by: Li, Gen, et al.
Published: (2021)
On the Uniform Convergence of Subdifferentials in Stochastic Optimization and Learning
by: Ruan, Feng
Published: (2024)
by: Ruan, Feng
Published: (2024)
Minimax and Bayes Optimal Best-Arm Identification
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Improving Minimax Estimation Rates for Contaminated Mixture of Multinomial Logistic Experts via Expert Heterogeneity
by: Yan, Fanqi, et al.
Published: (2026)
by: Yan, Fanqi, et al.
Published: (2026)
Bridging Maximum Likelihood and Optimal Transport for Efficient Inference and Model Selection in Stochastic Block Models
by: Queric, Simon, et al.
Published: (2026)
by: Queric, Simon, et al.
Published: (2026)
Extended Wasserstein-GAN Approach to Causal Distribution Learning: Density-Free Estimation and Minimax Optimality
by: Tamano, Shu, et al.
Published: (2026)
by: Tamano, Shu, et al.
Published: (2026)
Minimax Optimal Fair Classification with Bounded Demographic Disparity
by: Zeng, Xianli, et al.
Published: (2024)
by: Zeng, Xianli, et al.
Published: (2024)
$L^2$ over Wasserstein: Statistical Analysis for Optimal Transport
by: Passeggeri, Riccardo, et al.
Published: (2026)
by: Passeggeri, Riccardo, et al.
Published: (2026)
Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
by: Zhang, Kaihong, et al.
Published: (2024)
by: Zhang, Kaihong, et al.
Published: (2024)
Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning
by: Li, Gen, et al.
Published: (2023)
by: Li, Gen, et al.
Published: (2023)
Similar Items
-
Semi-Discrete Optimal Transport: Nearly Minimax Estimation With Stochastic Gradient Descent and Adaptive Entropic Regularization
by: Genans, Ferdinand, et al.
Published: (2024) -
Decreasing Entropic Regularization Averaged Gradient for Semi-Discrete Optimal Transport
by: Genans, Ferdinand, et al.
Published: (2025) -
Geometry-Aware Optimal Transport: Fast Intrinsic Dimension and Wasserstein Distance Estimation
by: Genans, Ferdinand, et al.
Published: (2026) -
Convergence in quadratic mean of averaged stochastic gradient algorithms without strong convexity nor bounded gradient
by: Godichon-Baggioni, Antoine
Published: (2021) -
A Full Adagrad algorithm with O(Nd) operations
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)