Differentiable Convex Optimization Layers

28 October 2019

Zico Kolter

Papers citing "Differentiable Convex Optimization Layers"

25 / 125 papers shown

Title
Differentiable Learning Under Triage Nastaran Okati A. De Manuel Gomez Rodriguez 26 63 0 16 Mar 2021
Strategic Classification Made Practical Sagi Levanon Nir Rosenfeld 40 55 0 02 Mar 2021
Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Policy Optimization Jyun-Li Lin Wei-Ting Hung Shangtong Yang Ping-Chun Hsieh Xi Liu 30 14 0 22 Feb 2021
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty 52 34 0 12 Feb 2021
Differentiable Trust Region Layers for Deep Reinforcement Learning Fabian Otto P. Becker Ngo Anh Vien Hanna Ziesche Gerhard Neumann OffRL 41 19 0 22 Jan 2021
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 27 101 0 09 Nov 2020
LCollision: Fast Generation of Collision-Free Human Poses using Learned Non-Penetration Constraints Qingyang Tan Zherong Pan Tianyi Zhou 3DH 30 10 0 06 Nov 2020
A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing Chunchuan Lyu Shay B. Cohen Ivan Titov 38 11 0 23 Oct 2020
Learning the Step-size Policy for the Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm Lucas N. Egidio A. Hansson B. Wahlberg 16 12 0 03 Oct 2020
On the Iteration Complexity of Hypergradient Computation Riccardo Grazzi Luca Franceschi Massimiliano Pontil Saverio Salzo 48 193 0 29 Jun 2020
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems Kai Wang Bryan Wilder Andrew Perrault Milind Tambe 21 28 0 18 Jun 2020
Learning Linear Programs from Optimal Decisions Yingcong Tan Daria Terekhov Andrew Delong 30 28 0 16 Jun 2020
Monotone operator equilibrium networks Ezra Winston J. Zico Kolter 32 130 0 15 Jun 2020
Gradient Estimation with Stochastic Softmax Tricks Max B. Paulus Dami Choi Daniel Tarlow Andreas Krause Chris J. Maddison BDL 36 85 0 15 Jun 2020
Distributionally Robust Weighted $k$ -Nearest Neighbors Shixiang Zhu Liyan Xie Minghe Zhang Rui Gao Yao Xie OOD 21 7 0 07 Jun 2020
Physarum Powered Differentiable Linear Programming Layers and Applications Zihang Meng Sathya Ravi Vikas Singh 23 5 0 30 Apr 2020
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow Zachary Teed Jia Deng MDE 68 2,550 0 26 Mar 2020
Differentiating through the Fréchet Mean Aaron Lou Isay Katsman Qingxuan Jiang Serge J. Belongie Ser-Nam Lim Christopher De Sa DRL 20 61 0 29 Feb 2020
Learning with Differentiable Perturbed Optimizers Quentin Berthet Mathieu Blondel O. Teboul Marco Cuturi Jean-Philippe Vert Francis R. Bach 29 105 0 20 Feb 2020
Lossless Compression of Deep Neural Networks Thiago Serra Abhinav Kumar Srikumar Ramalingam 24 56 0 01 Jan 2020
Learning Convex Optimization Control Policies Akshay Agrawal Shane T. Barratt Stephen P. Boyd Bartolomeo Stellato 30 66 0 19 Dec 2019
Minimizing a Sum of Clipped Convex Functions Shane T. Barratt Guillermo Angeris Stephen P. Boyd 10 9 0 27 Oct 2019
The Differentiable Cross-Entropy Method Brandon Amos Denis Yarats 29 54 0 27 Sep 2019
Least Squares Auto-Tuning Shane T. Barratt Stephen P. Boyd MoMe 19 23 0 10 Apr 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 362 11,700 0 09 Mar 2017