101 citations · 139 across the 6 of their papers we have counts for
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A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast
Jongmin Lee, Chanwoo Park, Ernest K. Ryu
Since Nesterov's seminal 1983 work, many accelerated first-order optimization methods have been proposed, but their analyses lacks a common unifying structure. In this work, we ide…
Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with Rate on Squared Gradient Norm
TaeHo Yoon, Ernest K. Ryu
In this work, we study the computational complexity of reducing the squared gradient magnitude for smooth minimax optimization problems. First, we present algorithms with accelerat…
Factor- Acceleration of Accelerated Gradient Methods
Chanwoo Park, Jisun Park, Ernest K. Ryu
The optimized gradient method (OGM) provides a factor- speedup upon Nesterov's celebrated accelerated gradient method in the convex (but non-strongly convex) setup. Howev…
Tight Coefficients of Averaged Operators via Scaled Relative Graph
Xinmeng Huang, Ernest K. Ryu, Wotao Yin
Many iterative methods in optimization are fixed-point iterations with averaged operators. As such methods converge at an rate with the constant determined by th…
Finding the forward-Douglas-Rachford-forward method
Ernest K. Ryu, Bang Cong Vu
We consider the monotone inclusion problem with a sum of 3 operators, in which 2 are monotone and 1 is monotone-Lipschitz. The classical Douglas--Rachford and Forward-backward-forw…
Decentralized Proximal Gradient Algorithms with Linear Convergence Rates
Sulaiman A. Alghunaim, Ernest K. Ryu, Kun Yuan +1
This work studies a class of non-smooth decentralized multi-agent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a c…