1 citations · 1 across the 3 of their papers we have counts for
3 papers
Almost Sure Convergence and Non-asymptotic Concentration Bounds for Stochastic Mirror Descent Algorithm
Anik Kumar Paul, Arun D Mahindrakar, Rachel K Kalaimani
This letter investigates the convergence and concentration properties of the Stochastic Mirror Descent (SMD) algorithm utilizing biased stochastic subgradients. We establish the al…
Convergence Analysis of Stochastic Saddle Point Mirror Descent Algorithm -- A Projected Dynamical View Point
Anik Kumar Paul, Arun D Mahindrakar, Rachel K Kalaimani
Saddle point problems, ubiquitous in optimization, extend beyond game theory to diverse domains like power networks and reinforcement learning. This paper presents novel approaches…
A Unified Framework for Consensus and Synchronization on Lie Groups admitting a Bi-Invariant Metric
Rama Seshan Chandrasekharan, Ravi N Banavar, Arun D Mahindrakar
For a finite number of agents evolving on a Euclidean space and linked to each other by a connected graph, the Laplacian flow that is based on the inter-agent errors, ensures conse…