81 citations · 264 across the 35 of their papers we have counts for
7 papers · 1 filter
Distributed gradient methods under heavy-tailed communication noise
Manojlo Vukovic, Dusan Jakovetic, Dragana Bajovic +1
We consider a standard distributed optimization problem in which networked nodes collaboratively minimize the sum of their locally known convex costs. For this setting, we address…
Nonlinear consensus+innovations under correlated heavy-tailed noises: Mean square convergence rate and asymptotics
Manojlo Vukovic, Dusan Jakovetic, Dragana Bajovic +1
We consider distributed recursive estimation of consensus+innovations type in the presence of heavy-tailed sensing and communication noises. We allow that the sensing and communica…
Nonlinear gradient mappings and stochastic optimization: A general framework with applications to heavy-tail noise
Dusan Jakovetic, Dragana Bajovic, Anit Kumar Sahu +3
We introduce a general framework for nonlinear stochastic gradient descent (SGD) for the scenarios when gradient noise exhibits heavy tails. The proposed framework subsumes several…
Primal-dual methods for large-scale and distributed convex optimization and data analytics
Dusan Jakovetic, Dragana Bajovic, Joao Xavier +1
The augmented Lagrangian method (ALM) is a classical optimization tool that solves a given "difficult" (constrained) problem via finding solutions of a sequence of "easier"(often u…
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…