OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression

27 May 2021

Papers citing "OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression"

22 / 22 papers shown

Title
A Tutorial on Distributed Optimization for Cooperative Robotics: from Setups and Algorithms to Toolboxes and Research Directions Andrea Testa Guido Carnevale G. Notarstefano 65 11 0 08 Sep 2023
Learning equilibria with personalized incentives in a class of nonmonotone games F. Fabiani Andrea Simonetto Paul Goulart 53 11 0 06 Nov 2021
Neural Fixed-Point Acceleration for Convex Optimization Shobha Venkataraman Brandon Amos 58 13 0 21 Jul 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 137 231 0 23 Mar 2021
Unifying Lower Bounds on Prediction Dimension of Consistent Convex Surrogates Jessie Finocchiaro Rafael Frongillo Bo Waggoner 65 4 0 16 Feb 2021
Regret minimization in stochastic non-convex learning via a proximal-gradient approach Nadav Hallak P. Mertikopoulos Volkan Cevher 19 20 0 13 Oct 2020
Regularization by Denoising via Fixed-Point Projection (RED-PRO) Regev Cohen Michael Elad P. Milanfar 47 106 0 01 Aug 2020
Deep Learning Techniques for Inverse Problems in Imaging Greg Ongie A. Jalal Christopher A. Metzler Richard G. Baraniuk A. Dimakis Rebecca Willett 63 526 0 12 May 2020
Socially-Aware Robot Planning via Bandit Human Feedback Xusheng Luo Yan Zhang Michael M. Zavlanos 40 17 0 02 Mar 2020
Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization Vien V. Mai M. Johansson 41 55 0 13 Feb 2020
Anderson Acceleration of Proximal Gradient Methods Vien V. Mai M. Johansson 32 36 0 18 Oct 2019
Optimization and Learning with Information Streams: Time-varying Algorithms and Applications E. Dall’Anese Andrea Simonetto Stephen Becker Liam Madden 70 69 0 17 Oct 2019
Multivariate Distributionally Robust Convex Regression under Absolute Error Loss Jose H. Blanchet Peter Glynn Jun Yan Zhengqing Zhou 25 31 0 29 May 2019
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport François-Pierre Paty Alexandre d’Aspremont Marco Cuturi OT 54 33 0 26 May 2019
Stochastic model-based minimization of weakly convex functions Damek Davis Dmitriy Drusvyatskiy 66 373 0 17 Mar 2018
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems Tim Meinhardt Michael Möller C. Hazirbas Daniel Cremers 61 357 0 11 Apr 2017
Stochastic Methods for Composite and Weakly Convex Optimization Problems John C. Duchi Feng Ruan 32 127 0 24 Mar 2017
A Computational Framework for Multivariate Convex Regression and its Variants Rahul Mazumder Arkopal Choudhury G. Iyengar B. Sen 80 82 0 28 Sep 2015
Convex Calibration Dimension for Multiclass Loss Matrices H. G. Ramaswamy S. Agarwal 43 47 0 12 Aug 2014
Non-stationary Stochastic Optimization Omar Besbes Y. Gur A. Zeevi 127 430 0 20 Jul 2013
Sparse Recovery of Streaming Signals Using L1-Homotopy M. Salman Asif Justin Romberg 65 155 0 14 Jun 2013
Nonparametric Least Squares Estimation of a Multivariate Convex Regression Function E. Seijo B. Sen 78 165 0 24 Mar 2010