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Sample Efficient Reinforcement Learning with REINFORCE

Oct 22, 2020
Junzi Zhang, Jongho Kim, Brendan O'Donoghue, Stephen Boyd

* 35 pages 

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Learning Convex Optimization Models

Jun 18, 2020
Akshay Agrawal, Shane Barratt, Stephen Boyd

* Authors listed in alphabetical order 

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Fitting Laplacian Regularized Stratified Gaussian Models

May 22, 2020
Jonathan Tuck, Stephen Boyd


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Optimal Representative Sample Weighting

May 18, 2020
Shane Barratt, Guillermo Angeris, Stephen Boyd


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Eigen-Stratified Models

Jan 27, 2020
Jonathan Tuck, Stephen Boyd


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Learning Convex Optimization Control Policies

Dec 19, 2019
Akshay Agrawal, Shane Barratt, Stephen Boyd, Bartolomeo Stellato

* Authors listed in alphabetical order 

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Minimizing a Sum of Clipped Convex Functions

Oct 29, 2019
Shane Barratt, Guillermo Angeris, Stephen Boyd


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Differentiable Convex Optimization Layers

Oct 28, 2019
Akshay Agrawal, Brandon Amos, Shane Barratt, Stephen Boyd, Steven Diamond, Zico Kolter

* In NeurIPS 2019. Code available at https://www.github.com/cvxgrp/cvxpylayers. Authors in alphabetical order 

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Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize

Oct 15, 2019
Youngsuk Park, Sauptik Dhar, Stephen Boyd, Mohak Shah


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A General Optimization Framework for Dynamic Time Warping

May 31, 2019
Dave Deriso, Stephen Boyd

* 22 pages, 11 figures 

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A Distributed Method for Fitting Laplacian Regularized Stratified Models

Apr 26, 2019
Jonathan Tuck, Shane Barratt, Stephen Boyd

* 37 pages, 6 figures 

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Least Squares Auto-Tuning

Apr 10, 2019
Shane Barratt, Stephen Boyd


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Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data

Oct 22, 2018
Shane Barratt, Mykel Kochenderfer, Stephen Boyd

* IEEE Transactions on Intelligent Transportation Systems 

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On the convergence of mirror descent beyond stochastic convex programming

Jul 16, 2018
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen Boyd, Peter Glynn

* 30 pages, 5 figures 

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Convolutional Imputation of Matrix Networks

Jun 07, 2018
Qingyun Sun, Mengyuan Yan David Donoho, Stephen Boyd

* Accepted by ICML 2018 

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Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

May 15, 2018
David Hallac, Sagar Vare, Stephen Boyd, Jure Leskovec

* This revised version fixes two small typos in the published version 

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Saturating Splines and Feature Selection

Dec 04, 2017
Nicholas Boyd, Trevor Hastie, Stephen Boyd, Benjamin Recht, Michael Jordan

* Adding missing references and related work 

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Network Inference via the Time-Varying Graphical Lasso

Jun 10, 2017
David Hallac, Youngsuk Park, Stephen Boyd, Jure Leskovec


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Dirty Pixels: Optimizing Image Classification Architectures for Raw Sensor Data

Jan 23, 2017
Steven Diamond, Vincent Sitzmann, Stephen Boyd, Gordon Wetzstein, Felix Heide


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A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights

Oct 27, 2015
Weijie Su, Stephen Boyd, Emmanuel J. Candes

* To appear in Journal of Machine Learning Research. Added more simulation studies. Preliminary version appeared in NIPS 2014 

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Generalized Low Rank Models

May 05, 2015
Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen Boyd

* 84 pages, 19 figures 

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Convex Optimization in Julia

Oct 17, 2014
Madeleine Udell, Karanveer Mohan, David Zeng, Jenny Hong, Steven Diamond, Stephen Boyd

* To appear in Proceedings of the Workshop on High Performance Technical Computing in Dynamic Languages (HPTCDL) 2014 

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An ADMM Algorithm for a Class of Total Variation Regularized Estimation Problems

Mar 08, 2012
Bo Wahlberg, Stephen Boyd, Mariette Annergren, Yang Wang


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