A proximally constrained subgradient method finds a nearly stationary point for weakly convex objectives with weakly convex constraints in O(1/epsilon^4) deterministic and O~(1/epsilon^6) stochastic iterations.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints
A proximally constrained subgradient method finds a nearly stationary point for weakly convex objectives with weakly convex constraints in O(1/epsilon^4) deterministic and O~(1/epsilon^6) stochastic iterations.