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On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
[article]
2019
arXiv
pre-print
Many tasks in modern machine learning can be formulated as finding equilibria in sequential games. In particular, two-player zero-sum sequential games, also known as minimax optimization, have received growing interest. It is tempting to apply gradient descent to solve minimax optimization given its popularity and success in supervised learning. However, it has been noted that naive application of gradient descent fails to find some local minimax and can converge to non-local-minimax points. In
arXiv:1910.07512v2
fatcat:5cmual4pnffxrl6dzzspkmbegm