54 citations · 225 across the 30 of their papers we have counts for
4 papers · 1 filter
A Stochastic Newton Algorithm for Distributed Convex Optimization
Brian Bullins, Kumar Kshitij Patel, Ohad Shamir +2
We propose and analyze a stochastic Newton algorithm for homogeneous distributed stochastic convex optimization, where each machine can calculate stochastic gradients of the same p…
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization
Deeksha Adil, Brian Bullins, Sushant Sachdeva
We provide several algorithms for constrained optimization of a large class of convex problems, including softmax, regression, and logistic regression. Central to our appr…
Almost-linear-time Weighted -norm Solvers in Slightly Dense Graphs via Sparsification
Deeksha Adil, Brian Bullins, Rasmus Kyng +1
We give almost-linear-time algorithms for constructing sparsifiers with edges that approximately preserve weighted flow or voltage obj…
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication
Blake Woodworth, Brian Bullins, Ohad Shamir +1
We resolve the min-max complexity of distributed stochastic convex optimization (up to a log factor) in the intermittent communication setting, where machines work in parallel…