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stochastic optimization

topic2 events
papersTODAY 04:00 UTC

arXiv Paper Analyzes Steady-State Convergence in Constant-StepSize Stochastic Approximation

A new arXiv preprint examines constant-stepsize stochastic approximation, where iterates settle into a stationary distribution that varies with the chosen stepsize. The work focuses on steady-state convergence, meaning the behavior of the rescaled stationary law as the stepsize shrinks toward zero. It is a theoretical contribution to the analysis of stochastic optimization algorithms rather than a released model or tool.

research/optimization/stochastic-approximation/arxiv
papersTODAY 04:00 UTC

Projection-Free Methods for Stochastic Constrained Compositional Optimization

A new arXiv paper develops projection-free algorithms for stochastic optimization problems whose objectives are nested compositions of smooth functions over a closed convex decision set. The work targets the multi-level compositional setting, where gradients must be estimated through several layers of functions. It aims to avoid costly projection steps while still handling constraints.

optimization/arxiv/theory/algorithms