Solving Zero-Sum Games with Fewer Matrix-Vector Products
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arXiv
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| Format: | Preprint |
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2025
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| author | Karmarkar, Ishani O'Carroll, Liam Sidford, Aaron |
| author_facet | Karmarkar, Ishani O'Carroll, Liam Sidford, Aaron |
| contents | In this paper we consider the problem of computing an $ε$-approximate Nash Equilibrium of a zero-sum game in a payoff matrix $A \in \mathbb{R}^{m \times n}$ with $O(1)$-bounded entries given access to a matrix-vector product oracle for $A$ and its transpose $A^\top$. We provide a deterministic algorithm that solves the problem using $\tilde{O}(ε^{-8/9})$-oracle queries, where $\tilde{O}(\cdot)$ hides factors polylogarithmic in $m$, $n$, and $ε^{-1}$. Our result improves upon the state-of-the-art query complexity of $\tilde{O}(ε^{-1})$ established by [Nemirovski, 2004] and [Nesterov, 2005]. We obtain this result through a general framework that yields improved deterministic query complexities for solving a broader class of minimax optimization problems which includes computing a linear classifier (hard-margin support vector machine) as well as linear regression. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_04426 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Solving Zero-Sum Games with Fewer Matrix-Vector Products Karmarkar, Ishani O'Carroll, Liam Sidford, Aaron Optimization and Control Data Structures and Algorithms Computer Science and Game Theory In this paper we consider the problem of computing an $ε$-approximate Nash Equilibrium of a zero-sum game in a payoff matrix $A \in \mathbb{R}^{m \times n}$ with $O(1)$-bounded entries given access to a matrix-vector product oracle for $A$ and its transpose $A^\top$. We provide a deterministic algorithm that solves the problem using $\tilde{O}(ε^{-8/9})$-oracle queries, where $\tilde{O}(\cdot)$ hides factors polylogarithmic in $m$, $n$, and $ε^{-1}$. Our result improves upon the state-of-the-art query complexity of $\tilde{O}(ε^{-1})$ established by [Nemirovski, 2004] and [Nesterov, 2005]. We obtain this result through a general framework that yields improved deterministic query complexities for solving a broader class of minimax optimization problems which includes computing a linear classifier (hard-margin support vector machine) as well as linear regression. |
| title | Solving Zero-Sum Games with Fewer Matrix-Vector Products |
| topic | Optimization and Control Data Structures and Algorithms Computer Science and Game Theory |
| url | https://arxiv.org/abs/2509.04426 |