3 papers
math.OC2026
Online Feedback Optimization for Constrained Stochastic Problems with Decision-Dependent Distributions: Extended Version
Caio Kalil Lauand, Emiliano Dall'Anese
Online feedback optimization (OFO) leverages real-time output measurements to optimize the operation of networked systems without requiring full knowledge of system dynamics or dis…
math.OC2025
Global Convergence and Acceleration for Single Observation Gradient Free Optimization
Caio Kalil Lauand, Sean Meyn
Simultaneous perturbation stochastic approximation (SPSA) is an approach to gradient-free optimization introduced by Spall as a simplification of the approach of Kiefer and Wolfowi…
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…