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math.OC2021
Minimax Optimization: The Case of Convex-Submodular
Arman Adibi, Aryan Mokhtari, Hamed Hassani
Minimax optimization has been central in addressing various applications in machine learning, game theory, and control theory. Prior literature has thus far mainly focused on study…
math.OC2021
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach
Qiujiang Jin, Aryan Mokhtari
In this paper, we study the application of quasi-Newton methods for solving empirical risk minimization (ERM) problems defined over a large dataset. Traditional deterministic and s…