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Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation


Sep 24, 2022
Xuesu Xiao, Tingnan Zhang, Krzysztof Choromanski, Edward Lee, Anthony Francis, Jake Varley, Stephen Tu, Sumeet Singh, Peng Xu, Fei Xia, Sven Mikael Persson, Dmitry Kalashnikov, Leila Takayama, Roy Frostig, Jie Tan, Carolina Parada, Vikas Sindhwani

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Learning from many trajectories


Mar 31, 2022
Stephen Tu, Roy Frostig, Mahdi Soltanolkotabi

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Efficient and Modular Implicit Differentiation


May 31, 2021
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert

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Decomposing reverse-mode automatic differentiation


May 20, 2021
Roy Frostig, Matthew J. Johnson, Dougal Maclaurin, Adam Paszke, Alexey Radul

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* Presented at the LAFI 2021 workshop at POPL, 17 January 2021 

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The advantages of multiple classes for reducing overfitting from test set reuse


May 24, 2019
Vitaly Feldman, Roy Frostig, Moritz Hardt

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Measuring the Effects of Data Parallelism on Neural Network Training


Nov 21, 2018
Christopher J. Shallue, Jaehoon Lee, Joseph Antognini, Jascha Sohl-Dickstein, Roy Frostig, George E. Dahl

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* Submitted to JMLR 

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Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity


May 19, 2017
Amit Daniely, Roy Frostig, Yoram Singer

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Random Features for Compositional Kernels


Mar 22, 2017
Amit Daniely, Roy Frostig, Vineet Gupta, Yoram Singer

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Estimation from Indirect Supervision with Linear Moments


Aug 10, 2016
Aditi Raghunathan, Roy Frostig, John Duchi, Percy Liang

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* 12 pages, 7 figures, extended and updated version of our paper appearing in ICML 2016 

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Principal Component Projection Without Principal Component Analysis


Feb 22, 2016
Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford

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