87 citations · 373 across the 33 of their papers we have counts for
6 papers · 1 filter
Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle
Dan Garber, Tsur Livney, Shoham Sabach
This paper considers a convex composite optimization problem with affine constraints, which includes problems that take the form of minimizing a smooth convex objective function ov…
Low-Rank Mirror-Prox for Nonsmooth and Low-Rank Matrix Optimization Problems
Dan Garber, Atara Kaplan
Low-rank and nonsmooth matrix optimization problems capture many fundamental tasks in statistics and machine learning. While significant progress has been made in recent years in d…
Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator
Lior Danon, Dan Garber
Tyler's M-estimator is a well known procedure for robust and heavy-tailed covariance estimation. Tyler himself suggested an iterative fixed-point algorithm for computing his estima…
New Projection-free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees
Dan Garber, Ben Kretzu
We present new efficient \textit{projection-free} algorithms for online convex optimization (OCO), where by projection-free we refer to algorithms that avoid computing orthogonal p…
Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems
Dan Garber, Atara Kaplan
Low-rank and nonsmooth matrix optimization problems capture many fundamental tasks in statistics and machine learning. While significant progress has been made in recent years in d…
Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity
Dan Garber, Ron Fisher
We consider optimization problems in which the goal is find a -dimensional subspace of , , which minimizes a convex and smooth loss. Such problems generalize…