170 citations · 395 across the 10 of their papers we have counts for
4 papers · 1 filter
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method
Yossi Arjevani, Joan Bruna, Bugra Can +3
We introduce a framework for designing primal methods under the decentralized optimization setting where local functions are smooth and strongly convex. Our approach consists of ap…
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity
Jingzhao Zhang, Hongzhou Lin, Subhro Das +2
We study oracle complexity of gradient based methods for stochastic approximation problems. Though in many settings optimal algorithms and tight lower bounds are known for such pro…
On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions
Yossi Arjevani, Amit Daniely, Stefanie Jegelka +1
Recent advances in randomized incremental methods for minimizing -smooth -strongly convex finite sums have culminated in tight complexity of $\tilde{O}((n+\sqrt{n L/μ})\log(1…
Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions
Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka +2
We provide the first non-asymptotic analysis for finding stationary points of nonsmooth, nonconvex functions. In particular, we study the class of Hadamard semi-differentiable func…