Unifying Distributionally Robust Optimization via Optimal Transport Theory
Fuente:
arXiv
Saved in:
| Main Authors: | Blanchet, Jose, Kuhn, Daniel, Li, Jiajin, Taskesen, Bahar |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Metrizing Fairness
by: Rychener, Yves, et al.
Published: (2022)
by: Rychener, Yves, et al.
Published: (2022)
Automatic Outlier Rectification via Optimal Transport
by: Blanchet, Jose, et al.
Published: (2024)
by: Blanchet, Jose, et al.
Published: (2024)
Optimal Transport on Lie Group Orbits
by: Taskesen, Bahar
Published: (2025)
by: Taskesen, Bahar
Published: (2025)
Stability Evaluation via Distributional Perturbation Analysis
by: Blanchet, Jose, et al.
Published: (2024)
by: Blanchet, Jose, et al.
Published: (2024)
Optimality of Linear Policies in Distributionally Robust Linear Quadratic Control
by: Taşkesen, Bahar, et al.
Published: (2025)
by: Taşkesen, Bahar, et al.
Published: (2025)
Wasserstein Distributionally Robust Regret Optimization
by: Fiechtner, Lukas-Benedikt, et al.
Published: (2025)
by: Fiechtner, Lukas-Benedikt, et al.
Published: (2025)
Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization
by: Shafiee, Soroosh, et al.
Published: (2023)
by: Shafiee, Soroosh, et al.
Published: (2023)
Distributionally Robust Optimization
by: Kuhn, Daniel, et al.
Published: (2024)
by: Kuhn, Daniel, et al.
Published: (2024)
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
by: Kuhn, Daniel, et al.
Published: (2019)
by: Kuhn, Daniel, et al.
Published: (2019)
On the Foundation of Distributionally Robust Reinforcement Learning
by: Wang, Shengbo, et al.
Published: (2023)
by: Wang, Shengbo, et al.
Published: (2023)
Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback
by: Wang, Yikai, et al.
Published: (2026)
by: Wang, Yikai, et al.
Published: (2026)
Sample Complexity of Variance-reduced Distributionally Robust Q-learning
by: Wang, Shengbo, et al.
Published: (2023)
by: Wang, Shengbo, et al.
Published: (2023)
Robustifying Conditional Portfolio Decisions via Optimal Transport
by: Nguyen, Viet Anh, et al.
Published: (2021)
by: Nguyen, Viet Anh, et al.
Published: (2021)
Optimal Sample Complexity for Average Reward Markov Decision Processes
by: Wang, Shengbo, et al.
Published: (2023)
by: Wang, Shengbo, et al.
Published: (2023)
Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond
by: Soma, Tasuku, et al.
Published: (2022)
by: Soma, Tasuku, et al.
Published: (2022)
A Unified Kantorovich Duality for Multimarginal Optimal Transport
by: Cheryala, Yehya, et al.
Published: (2026)
by: Cheryala, Yehya, et al.
Published: (2026)
On Generalization and Regularization via Wasserstein Distributionally Robust Optimization
by: Wu, Qinyu, et al.
Published: (2022)
by: Wu, Qinyu, et al.
Published: (2022)
Nonsmooth Nonconvex-Nonconcave Minimax Optimization: Primal-Dual Balancing and Iteration Complexity Analysis
by: Li, Jiajin, et al.
Published: (2022)
by: Li, Jiajin, et al.
Published: (2022)
Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity
by: Shi, Qiankun, et al.
Published: (2025)
by: Shi, Qiankun, et al.
Published: (2025)
Robust Assortment Optimization from Observational Data
by: Lu, Miao, et al.
Published: (2026)
by: Lu, Miao, et al.
Published: (2026)
Robust Out-of-Distribution Stochastic Optimization
by: Li, Xianyu, et al.
Published: (2026)
by: Li, Xianyu, et al.
Published: (2026)
A Tight Theory of Error Feedback Algorithms in Distributed Optimization
by: Thomsen, Daniel Berg, et al.
Published: (2026)
by: Thomsen, Daniel Berg, et al.
Published: (2026)
On the Width Scaling of Neural Optimizers Under Matrix Operator Norms I: Row/Column Normalization and Hyperparameter Transfer
by: Xu, Ruihan, et al.
Published: (2026)
by: Xu, Ruihan, et al.
Published: (2026)
Duality and Policy Evaluation in Distributionally Robust Bayesian Diffusion Control
by: Blanchet, Jose, et al.
Published: (2025)
by: Blanchet, Jose, et al.
Published: (2025)
Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent
by: Sun, Yihang, et al.
Published: (2026)
by: Sun, Yihang, et al.
Published: (2026)
Nonlinear Distributionally Robust Optimization
by: Sheriff, Mohammed Rayyan, et al.
Published: (2023)
by: Sheriff, Mohammed Rayyan, et al.
Published: (2023)
Distributionally-Robust Learning to Optimize
by: Ranjan, Vinit, et al.
Published: (2026)
by: Ranjan, Vinit, et al.
Published: (2026)
Sinkhorn Distributionally Robust Optimization
by: Wang, Jie, et al.
Published: (2021)
by: Wang, Jie, et al.
Published: (2021)
Distributionally Robust Optimization via Iterative Algorithms in Continuous Probability Spaces
by: Zhu, Linglingzhi, et al.
Published: (2024)
by: Zhu, Linglingzhi, et al.
Published: (2024)
Learning Optimal Classification Trees Robust to Distribution Shifts
by: Justin, Nathan, et al.
Published: (2023)
by: Justin, Nathan, et al.
Published: (2023)
Optimal Rates for Robust Stochastic Convex Optimization
by: Gao, Changyu, et al.
Published: (2024)
by: Gao, Changyu, et al.
Published: (2024)
A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set
by: Yue, Man-Chung, et al.
Published: (2024)
by: Yue, Man-Chung, et al.
Published: (2024)
Group Distributionally Robust Optimization with Flexible Sample Queries
by: Bai, Haomin, et al.
Published: (2025)
by: Bai, Haomin, et al.
Published: (2025)
Distributionally Robust Multi-Objective Optimization
by: Yang, Yufeng, et al.
Published: (2026)
by: Yang, Yufeng, et al.
Published: (2026)
Sobolev Gradient Ascent for Optimal Transport: Barycenter Optimization and Convergence Analysis
by: Kim, Kaheon, et al.
Published: (2025)
by: Kim, Kaheon, et al.
Published: (2025)
Distributionally Robust Regret Optimal LQR with Common Stage-Law Ambiguity
by: Fiechtner, Lukas-Benedikt, et al.
Published: (2026)
by: Fiechtner, Lukas-Benedikt, et al.
Published: (2026)
Optimal Data Splitting in Distributed Optimization for Machine Learning
by: Medyakov, Daniil, et al.
Published: (2024)
by: Medyakov, Daniil, et al.
Published: (2024)
Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms
by: Chen, He, et al.
Published: (2024)
by: Chen, He, et al.
Published: (2024)
Byzantine-Robust Distributed SGD: A Unified Analysis and Tight Error Bounds
by: Ruan, Boyuan, et al.
Published: (2026)
by: Ruan, Boyuan, et al.
Published: (2026)
Learning an Optimal Assortment Policy under Observational Data
by: Han, Yuxuan, et al.
Published: (2025)
by: Han, Yuxuan, et al.
Published: (2025)
Similar Items
-
Metrizing Fairness
by: Rychener, Yves, et al.
Published: (2022) -
Automatic Outlier Rectification via Optimal Transport
by: Blanchet, Jose, et al.
Published: (2024) -
Optimal Transport on Lie Group Orbits
by: Taskesen, Bahar
Published: (2025) -
Stability Evaluation via Distributional Perturbation Analysis
by: Blanchet, Jose, et al.
Published: (2024) -
Optimality of Linear Policies in Distributionally Robust Linear Quadratic Control
by: Taşkesen, Bahar, et al.
Published: (2025)