pith:IRZQA5WS
A Quadratic-Approximation-Based Stochastic Approximation Method for Weakly Convex Stochastic Programming
PMQSopt integrates proximal multipliers with quadratic approximations to reach O(T^{-1/4}) expected convergence on KKT metrics for weakly convex stochastic programs.
arxiv:2605.03400 v2 · 2026-05-05 · math.OC
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Claims
For each of these metrics, we establish an expected convergence rate of O(T^{-1/4}) after T iterations. Furthermore, we show that with probability at least 1-1/T^{2/3}, the gradient of the Lagrangian satisfies an O(T^{-1/8}) bound; with probability at least 1-2/T^{2/3}, the constraint violation achieves an O(T^{-1/4}) bound; and with probability at least 1-3/T^{2/3}, the complementarity violation attains an O(T^{-1/4}) bound.
All results are established under two mild conditions: (i) weak convexity of all problem functions, and (ii) the existence of a strictly feasible point.
PMQSopt achieves expected O(T^{-1/4}) convergence rates for three epsilon-KKT metrics after T iterations in weakly convex stochastic programming under weak convexity and strict feasibility assumptions.
Receipt and verification
| First computed | 2026-06-29T01:14:32.771397Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
44730076d2def4fc008babfd76460d239e336100378a6d3e722f4670db71bb75
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/IRZQA5WS332PYAELVP6XMRQNEO \
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Canonical record JSON
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