25 citations · 64 across the 20 of their papers we have counts for
6 papers · 2 filters
Towards Gradient Free and Projection Free Stochastic Optimization
Anit Kumar Sahu, Manzil Zaheer, Soummya Kar
This paper focuses on the problem of \emph{constrained} \emph{stochastic} optimization. A zeroth order Frank-Wolfe algorithm is proposed, which in addition to the projection-free n…
Communication-Efficient Distributed Strongly Convex Stochastic Optimization: Non-Asymptotic Rates
Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic +1
We examine fundamental tradeoffs in iterative distributed zeroth and first order stochastic optimization in multi-agent networks in terms of \emph{communication cost} (number of pe…
Distributed Zeroth Order Optimization Over Random Networks: A Kiefer-Wolfowitz Stochastic Approximation Approach
Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic +1
We study a standard distributed optimization framework where networked nodes collaboratively minimize the sum of their local convex costs. The main body of existing work consid…
Convergence rates for distributed stochastic optimization over random networks
Dusan Jakovetic, Dragana Bajovic, Anit Kumar Sahu +1
We establish the O() convergence rate for distributed stochastic gradient methods that operate over strongly convex costs and random networks. The considered class of…
: A Distributed Random Fields Estimator
Anit Kumar Sahu, Dusan Jakovetic, Soummya Kar
This paper presents a communication efficient distributed algorithm, of the \emph{consensus}+\emph{innovations} type, to estimate a high-dimensional parameter in…
Communication Optimality Trade-offs For Distributed Estimation
Anit Kumar Sahu, Dusan Jakovetic, Soummya Kar
This paper proposes ommunication efficient cursive istributed estimatin algorithm, , for networked multi-worker se…