91 citations · 113 across the 13 of their papers we have counts for
4 papers · 1 filter
Operator Splitting for Learning to Predict Equilibria in Convex Games
Daniel McKenzie, Howard Heaton, Qiuwei Li +3
Systems of competing agents can often be modeled as games. Assuming rationality, the most likely outcomes are given by an equilibrium (e.g. a Nash equilibrium). In many practical s…
Feasibility-based Fixed Point Networks
Howard Heaton, Samy Wu Fung, Aviv Gibali +1
Inverse problems consist of recovering a signal from a collection of noisy measurements. These problems can often be cast as feasibility problems; however, additional regularizatio…
Learning to Optimize: A Primer and A Benchmark
Tianlong Chen, Xiaohan Chen, Wuyang Chen +4
Learning to optimize (L2O) is an emerging approach that leverages machine learning to develop optimization methods, aiming at reducing the laborious iterations of hand engineering.…
JFB: Jacobian-Free Backpropagation for Implicit Networks
Samy Wu Fung, Howard Heaton, Qiuwei Li +3
A promising trend in deep learning replaces traditional feedforward networks with implicit networks. Unlike traditional networks, implicit networks solve a fixed point equation to…