Proves hardness of hyper-gradient stationarity for zero-respecting algorithms in nonconvex-convex bilevel optimization and establishes improved optimal complexity bounds under PL condition for nonconvex-nonconvex cases.
F or this problem, any algorithm with a procedure as Algorith m 1 stays at xt = 0 for any iteration numbert ≤ T
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On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis
Proves hardness of hyper-gradient stationarity for zero-respecting algorithms in nonconvex-convex bilevel optimization and establishes improved optimal complexity bounds under PL condition for nonconvex-nonconvex cases.