362 citations · 2.5k across the 76 of their papers we have counts for
5 papers · 2 filters
Conditional Gradient Methods
Gábor Braun, Alejandro Carderera, Cyrille W. Combettes +4
The purpose of this survey is to serve both as a gentle introduction and a coherent overview of state-of-the-art Frank--Wolfe algorithms, also called conditional gradient algorithm…
A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem
Ruichen Jiang, Nazanin Abolfazli, Aryan Mokhtari +1
In this paper, we study a class of bilevel optimization problems, also known as simple bilevel optimization, where we minimize a smooth objective function over the optimal solution…
Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models
Qiujiang Jin, Tongzheng Ren, Nhat Ho +1
The gradient descent (GD) method has been used widely to solve parameter estimation in generalized linear models (GLMs), a generalization of linear models when the link function ca…
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood
Qiujiang Jin, Alec Koppel, Ketan Rajawat +1
Non-asymptotic analysis of quasi-Newton methods have gained traction recently. In particular, several works have established a non-asymptotic superlinear rate of $\mathcal{O}((1/\s…
Generalized Optimistic Methods for Convex-Concave Saddle Point Problems
Ruichen Jiang, Aryan Mokhtari
The optimistic gradient method has seen increasing popularity for solving convex-concave saddle point problems. To analyze its iteration complexity, a recent work [arXiv:1906.01115…