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math.OC2024
Markovian Foundations for Quasi-Stochastic Approximation in Two Timescales: Extended Version
Caio Kalil Lauand, Sean Meyn
Many machine learning and optimization algorithms can be cast as instances of stochastic approximation (SA). The convergence rate of these algorithms is known to be slow, with the…
math.ST2024
Revisiting Step-Size Assumptions in Stochastic Approximation
Caio Kalil Lauand, Sean Meyn
Many machine learning and optimization algorithms are built upon the framework of stochastic approximation (SA), for which the selection of step-size (or learning rate) i…