9 citations · 10 across the 2 of their papers we have counts for
4 papers
A Different Perspective On The Stochastic Convex Feasibility Problem
James Renegar, Song Zhou
We analyze a simple randomized subgradient method for approximating solutions to stochastic systems of convex functional constraints, the only input to the algorithm being the size…
A Simple Nearly-Optimal Restart Scheme For Speeding-Up First Order Methods
James Renegar, Benjamin Grimmer
We present a simple scheme for restarting first-order methods for convex optimization problems. Restarts are made based only on achieving specified decreases in objective values, t…
"Efficient" Subgradient Methods for General Convex Optimization
James Renegar
A subgradient method is presented for solving general convex optimization problems, the main requirement being that a strictly-feasible point is known. A feasible sequence of itera…
A Framework for Applying Subgradient Methods to Conic Optimization Problems
James Renegar
A framework is presented whereby a general convex conic optimization problem is transformed into an equivalent convex optimization problem whose only constraints are linear equatio…