Requiring LICQ/SCS/SOSC everywhere in bilevel optimization is non-prevalent and rigid, while holding almost everywhere is prevalent, but the distinction introduces fundamental difficulties.
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A barrier-smoothed first-order method achieves stationarity rates of tilde O(K to the -2/3) deterministic and tilde O(K to the -2/5) stochastic for linearly constrained bilevel optimization.
Establishes exponential convergence in Wasserstein distance for the mean-field limit and finite-particle approximation of a consensus-based method solving nonconvex bi-level optimization problems.
citing papers explorer
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On the Nature of Regularity Assumptions in Bilevel Optimization with Constrained Lower-level Problem
Requiring LICQ/SCS/SOSC everywhere in bilevel optimization is non-prevalent and rigid, while holding almost everywhere is prevalent, but the distinction introduces fundamental difficulties.
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A Barrier-Metric First-Order Method for Linearly Constrained Bilevel Optimization
A barrier-smoothed first-order method achieves stationarity rates of tilde O(K to the -2/3) deterministic and tilde O(K to the -2/5) stochastic for linearly constrained bilevel optimization.
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Convergence of Consensus-Based Particle Methods for Nonconvex Bi-Level Optimization
Establishes exponential convergence in Wasserstein distance for the mean-field limit and finite-particle approximation of a consensus-based method solving nonconvex bi-level optimization problems.