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stochastic approximation

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

arXiv Paper Analyzes Constant-StepSize Nonsmooth Contractive Stochastic Approximation

The paper studies nonsmooth contractive stochastic approximation with a constant step size, motivated by Q-learning. It examines both additive-noise dynamics and synchronous as well as asynchronous variants, establishing steady-state convergence through a prelimit coupling method. The work is an updated arXiv submission.

stochastic-approximation/q-learning/optimization/arxiv