101 citations · 135 across the 4 of their papers we have counts for
5 papers
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers
Ernest K. Ryu, Jialin Liu, Sicheng Wang +3
Plug-and-play (PnP) is a non-convex framework that integrates modern denoising priors, such as BM3D or deep learning-based denoisers, into ADMM or other proximal algorithms. An adv…
Proximal-Proximal-Gradient Method
Ernest K. Ryu, Wotao Yin
In this paper, we present the proximal-proximal-gradient method (PPG), a novel optimization method that is simple to implement and simple to parallelize. PPG generalizes the proxim…
A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs
Yanli Liu, Ernest K. Ryu, Wotao Yin
In this paper, we present a method for identifying infeasible, unbounded, and pathological conic programs based on Douglas-Rachford splitting, or equivalently ADMM. When an optimiz…
Risk-Constrained Kelly Gambling
Enzo Busseti, Ernest K. Ryu, Stephen Boyd
We consider the classic Kelly gambling problem with general distribution of outcomes, and an additional risk constraint that limits the probability of a drawdown of wealth to a giv…
Stochastic Kronecker Graph on Vertex-Centric BSP
Ernest Ryu, Sean Choi
Recently Stochastic Kronecker Graph (SKG), a network generation model, and vertex-centric BSP, a graph processing framework like Pregel, have attracted much attention in the networ…