Image de couverture de livre

Blackwell's Approachability with Approximation Algorithms

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Garber, Dan, Massalha, Mhna
Format:	Preprint
Publié:	2025
Sujets:	Optimization and Control Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Accelerated Frank-Wolfe Algorithms: Complementarity Conditions and Sparsity
par: Garber, Dan
Publié: (2025)

A Randomized Linearly Convergent Frank-Wolfe-type Method for Smooth Convex Minimization over the Spectrahedron
par: Garber, Dan
Publié: (2025)

First-Order Sparse Convex Optimization: Better Rates with Sparse Updates
par: Garber, Dan
Publié: (2025)

Time-Dependent Blackwell Approachability and Application to Absorbing Games
par: Kwon, Joon, et autres
Publié: (2023)

Projection-Free Online Convex Optimization with Time-Varying Constraints
par: Garber, Dan, et autres
Publié: (2024)

Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems
par: Garber, Dan, et autres
Publié: (2022)

Low-Rank Extragradient Methods for Scalable Semidefinite Optimization
par: Garber, Dan, et autres
Publié: (2024)

Low-Rank Mirror-Prox for Nonsmooth and Low-Rank Matrix Optimization Problems
par: Garber, Dan, et autres
Publié: (2022)

Scalable Approximate Algorithms for Optimal Transport Linear Models
par: Kacprzak, Tomasz, et autres
Publié: (2025)

Weak Proximal Newton Oracles for Composite Convex Optimization
par: Garber, Dan
Publié: (2025)

Online Uniform Sampling: Randomized Learning-Augmented Approximation Algorithms with Application to Digital Health
par: Liu, Xueqing, et autres
Publié: (2024)

A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
par: Zhao, Heyang, et autres
Publié: (2023)

Approximate FW Algorithm with a novel DMO method over Graph-structured Support Set
par: Pan, Yijian, et autres
Publié: (2024)

Variational Theory and Algorithms for a Class of Asymptotically Approachable Nonconvex Problems
par: Li, Hanyang, et autres
Publié: (2023)

Improved Approximation Algorithms for Orthogonally Constrained Problems Using Semidefinite Optimization
par: Cory-Wright, Ryan, et autres
Publié: (2025)

Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation
par: Levin, Ilya, et autres
Publié: (2026)

Follow The Approximate Sparse Leader for No-Regret Online Sparse Linear Approximation
par: Mukhopadhyay, Samrat, et autres
Publié: (2025)

Tame Riemannian Stochastic Approximation
par: Aspman, Johannes, et autres
Publié: (2023)

Exponential Concentration in Stochastic Approximation
par: Law, Kody, et autres
Publié: (2022)

Rate-Preserving Reductions for Blackwell Approachability
par: Dann, Christoph, et autres
Publié: (2024)

Mathematical Programming Algorithms for Convex Hull Approximation with a Hyperplane Budget
par: Barbato, Michele, et autres
Publié: (2024)

Benchmarking Stochastic Approximation Algorithms for Fairness-Constrained Training of Deep Neural Networks
par: Kliachkin, Andrii, et autres
Publié: (2025)

Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
par: Cohen, Jeremy E., et autres
Publié: (2024)

Stochastic Approximation with Block Coordinate Optimal Stepsizes
par: Jiang, Tao, et autres
Publié: (2025)

Online Covariance Estimation in Nonsmooth Stochastic Approximation
par: Jiang, Liwei, et autres
Publié: (2025)

Gradient-Normalized Smoothness for Optimization with Approximate Hessians
par: Semenov, Andrei, et autres
Publié: (2025)

Random Features Approximation for Control-Affine Systems
par: Kazemian, Kimia, et autres
Publié: (2024)

Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
par: Rathore, Pratik, et autres
Publié: (2025)

Stochastic Approximation Methods for Distortion Risk Measure Optimization
par: Jiang, Jinyang, et autres
Publié: (2025)

Tractable Representations for Convergent Approximation of Distributional HJB Equations
par: Alhosh, Julie, et autres
Publié: (2025)

Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
par: Dong, Youran, et autres
Publié: (2025)

Weakly Time-Coupled Approximation of Markov Decision Processes
par: Soheili, Negar, et autres
Publié: (2026)

Black-Box Approximation and Optimization with Hierarchical Tucker Decomposition
par: Ryzhakov, Gleb, et autres
Publié: (2024)

Efficient Stochastic Approximation of Minimax Excess Risk Optimization
par: Zhang, Lijun, et autres
Publié: (2023)

Reinforcement Learning with Function Approximation for Non-Markov Processes
par: Kara, Ali Devran
Publié: (2026)

Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise
par: Chen, Zaiwei, et autres
Publié: (2023)

How Transformers Get Rich: Approximation and Dynamics Analysis
par: Wang, Mingze, et autres
Publié: (2024)

A Retrospective Approximation Approach for Smooth Stochastic Optimization
par: Newton, David, et autres
Publié: (2021)

Quantitative Flow Approximation Properties of Narrow Neural ODEs
par: Elamvazhuthi, Karthik
Publié: (2025)

Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
par: Sherman, Uri, et autres
Publié: (2025)