Roy Frostig

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 21

Top Topics

Data Parallelism

Top Venues

Publications

Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin
You Only Linearize Once: Tangents Transpose to Gradients. Proc. ACM Program. Lang. 7 (POPL) (2023)
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert
Efficient and Modular Implicit Differentiation. NeurIPS (2022)
Xuesu Xiao, Tingnan Zhang, Krzysztof Choromanski, Tsang-Wei Edward Lee, Anthony G. 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
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. CoRR (2022)
Xuesu Xiao, Tingnan Zhang, Krzysztof Marcin Choromanski, Tsang-Wei Edward Lee, Anthony G. 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
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. CoRL (2022)
Stephen Tu, Roy Frostig, Mahdi Soltanolkotabi
Learning from many trajectories. CoRR (2022)
Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin
You Only Linearize Once: Tangents Transpose to Gradients. CoRR (2022)
Adam Paszke, Matthew J. Johnson, Roy Frostig, Dougal Maclaurin
Parallelism-preserving automatic differentiation for second-order array languages. FHPNC@ICFP (2021)
Roy Frostig, Matthew J. Johnson, Dougal Maclaurin, Adam Paszke, Alexey Radul
Decomposing reverse-mode automatic differentiation. CoRR (2021)
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert
Efficient and Modular Implicit Differentiation. CoRR (2021)
Vitaly Feldman, Roy Frostig, Moritz Hardt
The advantages of multiple classes for reducing overfitting from test set reuse. CoRR (2019)
Vitaly Feldman, Roy Frostig, Moritz Hardt
The advantages of multiple classes for reducing overfitting from test set reuse. ICML (2019)
Christopher J. Shallue, Jaehoon Lee, Joseph M. Antognini, Jascha Sohl-Dickstein, Roy Frostig, George E. Dahl
Measuring the Effects of Data Parallelism on Neural Network Training. J. Mach. Learn. Res. 20 (2019)
Vitaly Feldman, Roy Frostig, Moritz Hardt
Open Problem: How fast can a multiclass test set be overfit? COLT (2019)
Christopher J. Shallue, Jaehoon Lee, Joseph M. Antognini, Jascha Sohl-Dickstein, Roy Frostig, George E. Dahl
Measuring the Effects of Data Parallelism on Neural Network Training. CoRR (2018)
Amit Daniely, Roy Frostig, Vineet Gupta, Yoram Singer
Random Features for Compositional Kernels. CoRR (2017)
Amit Daniely, Roy Frostig, Yoram Singer
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity. NIPS (2016)
Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford
Principal Component Projection Without Principal Component Analysis. ICML (2016)
Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford
Principal Component Projection Without Principal Component Analysis. CoRR (2016)
Aditi Raghunathan, Roy Frostig, John C. Duchi, Percy Liang
Estimation from Indirect Supervision with Linear Moments. CoRR (2016)
Amit Daniely, Roy Frostig, Yoram Singer
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity. CoRR (2016)
Aditi Raghunathan, Roy Frostig, John C. Duchi, Percy Liang
Estimation from Indirect Supervision with Linear Moments. ICML (2016)
Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford
Competing with the Empirical Risk Minimizer in a Single Pass. COLT (2015)
Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization. ICML (2015)
Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization. CoRR (2015)
Roy Frostig, Sida I. Wang
A sub-constant improvement in approximating the positive semidefinite Grothendieck problem. CoRR (2014)
Sida I. Wang, Roy Frostig, Percy Liang, Christopher D. Manning
Relaxations for inference in restricted Boltzmann machines. ICLR (Workshop) (2014)
Roy Frostig, Sida I. Wang, Percy Liang, Christopher D. Manning
Simple MAP Inference via Low-Rank Relaxations. NIPS (2014)
Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford
Competing with the Empirical Risk Minimizer in a Single Pass. CoRR (2014)
Jonathan Berant, Andrew Chou, Roy Frostig, Percy Liang
Semantic Parsing on Freebase from Question-Answer Pairs. EMNLP (2013)