Abstract
Deciding whether saddle points exist or are approximable for nonconvex-nonconcave problems is usually intractable. This paper takes a step towards understanding a broad class of nonconvex-nonconcave minimax problems that do remain tractable. Specifically, it studies minimax problems over geodesic metric spaces, which provide a vast generalization of the usual convex-concave saddle point problems. The first main result of the paper is a geodesic metric space version of Sion's minimax theorem; we believe our proof is novel and broadly accessible as it relies on the finite intersection property alone. The second main result is a specialization to geodesically complete Riemannian manifolds: here, we devise and analyze the complexity of first-order methods for smooth minimax problems.
| Original language | English |
|---|---|
| Pages (from-to) | 2885-2908 |
| Number of pages | 24 |
| Journal | SIAM Journal on Optimization |
| Volume | 33 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2023 |
| Externally published | Yes |
Keywords
- Riemannian optimization
- extragradient
- game theory
- geodesic convexity
- minimax
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