5 papers
Implicit Primal-Dual Guarantees in Unconstrained First-Order Minimization
Benjamin Grimmer, Alex L. Wang
This work considers the design of first-order convex optimization algorithms and convergence proofs. In particular, we consider nonsmooth Lipschitz and smooth problems accessed thr…
Beyond Minimax Optimality: A Subgame Perfect Gradient Method
Benjamin Grimmer, Kevin Shu, Alex L. Wang
The study of convex optimization has historically been concerned with worst-case convergence rates. The development of the Optimized Gradient Method (OGM), due to \citet{drori2012P…
Online learning of smooth functions on
Jesse Geneson, Kuldeep Singh, Alexander Wang
We study adversarial online learning of real-valued functions on . In each round the learner is queried at , predicts , and then observes th…
Subgame Perfect Methods in Nonsmooth Convex Optimization
Benjamin Grimmer, Alex L. Wang
This paper considers nonsmooth convex optimization with either a subgradient or proximal operator oracle. In both settings, we identify algorithms that achieve the recently introdu…
Composing Optimized Stepsize Schedules for Gradient Descent
Benjamin Grimmer, Kevin Shu, Alex L. Wang
Recent works by Altschuler and Parrilo and the authors have shown that it is possible to accelerate the convergence of gradient descent on smooth convex functions, even without mom…