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math.OC2026
Stochastic Mirror Descent under Iterate-Dependent Markov Noise: Analysis in the Asymptotic and Finite Time Regimes
Anik Kumar Paul, Shalabh Bhatnagar
We study a stochastic optimization problem in which the sampling distribution depends on the decision variable, and the available samples are generated through an iterate-dependent…
cs.LG2026
Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates
Anik Kumar Paul, Nibedita Roy, Nagesh Talagani +3
We propose FAR-SIGN (Fully Asynchronous Robust optimization via SIGNed directional projections) for adversary-resilient learning in parameter-server--worker systems. FAR-SIGN achie…
math.OC2026
Stochastic Recursive Inclusions under Biased Perturbations: An Input-to-State Stability Perspective
Anik Kumar Paul, Karthik Shenoy, Arun D. Mahindrakar
This paper investigates the asymptotic behavior of stochastic recursive inclusions in the presence of non-zero, non-diminishing bias, a setting that frequently arises in zeroth-ord…