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01/31/2023
Faster Predict-and-Optimize with Three-Operator Splitting
In many practical settings, a combinatorial problem must be repeatedly s...
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04/29/2022
Explainable AI via Learning to Optimize
Indecipherable black boxes are common in machine learning (ML), but appl...
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06/02/2021
Learn to Predict Equilibria via Fixed Point Networks
Systems of interacting agents can often be modeled as contextual games, ...
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04/29/2021
Feasibility-based Fixed Point Networks
Inverse problems consist of recovering a signal from a collection of noi...
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03/23/2021
Learning to Optimize: A Primer and A Benchmark
Learning to optimize (L2O) is an emerging approach that leverages machin...
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03/23/2021
Fixed Point Networks: Implicit Depth Models with Jacobian-Free Backprop
A growing trend in deep learning replaces fixed depth models by approxim...
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08/05/2020
Projecting to Manifolds via Unsupervised Learning
We present a new framework, called adversarial projections, for solving ...
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03/04/2020