3 papers
math.OC2025
An Adaptive and Parameter-Free Nesterov's Accelerated Gradient Method for Convex Optimization
Jaewook J. Suh, Shiqian Ma
We propose AdaNAG, an adaptive accelerated gradient method based on Nesterov's accelerated gradient method. AdaNAG is line-search-free, parameter-free, and achieves the accelerated…
math.OC2024
Optimization Algorithm Design via Electric Circuits
Stephen P. Boyd, Tetiana Parshakova, Ernest K. Ryu +1
We present a novel methodology for convex optimization algorithm design using ideas from electric RLC circuits. Given an optimization problem, the first stage of the methodology is…
math.OC2024
Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique
TaeHo Yoon, Jaeyeon Kim, Jaewook J. Suh +1
Recently, accelerated algorithms using the anchoring mechanism for minimax optimization and fixed-point problems have been proposed, and matching complexity lower bounds establish…