5 citations · 20 across the 29 of their papers we have counts for
3 papers · 2 filters
Extracting Dual Solutions via Primal Optimizers
Yair Carmon, Arun Jambulapati, Liam O'Carroll +1
We provide a general method to convert a "primal" black-box algorithm for solving regularized convex-concave minimax optimization problems into an algorithm for solving the associa…
Convex optimization with -norm oracles
Deeksha Adil, Brian Bullins, Arun Jambulapati +1
In recent years, there have been significant advances in efficiently solving -regression using linear system solvers and -regression [Adil-Kyng-Peng-Sachdeva, J. AC…
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization
Arun Jambulapati, Aaron Sidford, Kevin Tian
We develop a new parallel algorithm for minimizing Lipschitz, convex functions with a stochastic subgradient oracle. The total number of queries made and the query depth, i.e., the…