Semantic Parsing on Freebase from Question-Answer Pairs. - Jonathan Berant; Andrew Chou; Roy Frostig; Percy Liang (EMNLP, 2013)

Simple MAP Inference via Low-Rank Relaxations. - Roy Frostig; Sida Wang 001; Percy Liang; Christopher D. Manning (NIPS, 2014)

A sub-constant improvement in approximating the positive semidefinite Grothendieck problem. - Roy Frostig; Sida I. Wang (CoRR, 2014)

Relaxations for inference in restricted Boltzmann machines. - Sida I. Wang; Roy Frostig; Percy Liang; Christopher D. Manning (ICLR (Workshop), 2014)

Competing with the Empirical Risk Minimizer in a Single Pass. - Roy Frostig; Rong Ge 001; Sham M. Kakade; Aaron Sidford (COLT, 2015)

Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization. - Roy Frostig; Rong Ge 001; Sham M. Kakade; Aaron Sidford (ICML, 2015)

Principal Component Projection Without Principal Component Analysis. - Roy Frostig; Cameron Musco; Christopher Musco; Aaron Sidford (ICML, 2016)

Estimation from Indirect Supervision with Linear Moments. - Aditi Raghunathan; Roy Frostig; John C. Duchi; Percy Liang (ICML, 2016)

Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity. - Amit Daniely; Roy Frostig; Yoram Singer (NIPS, 2016)

Random Features for Compositional Kernels. - Amit Daniely; Roy Frostig; Vineet Gupta 001; Yoram Singer (CoRR, 2017)

Lightweight statistical learning : accelerating and avoiding empirical risk minimization. - Roy Frostig (2017)

Open Problem: How fast can a multiclass test set be overfit? - Vitaly Feldman; Roy Frostig; Moritz Hardt (COLT, 2019)

The advantages of multiple classes for reducing overfitting from test set reuse. - Vitaly Feldman; Roy Frostig; Moritz Hardt (ICML, 2019)

Measuring the Effects of Data Parallelism on Neural Network Training. - Christopher J. Shallue; Jaehoon Lee 001; Joseph M. Antognini; Jascha Sohl-Dickstein; Roy Frostig; George E. Dahl (J. Mach. Learn. Res., 2019)

Parallelism-preserving automatic differentiation for second-order array languages. - Adam Paszke; Matthew J. Johnson 002; Roy Frostig; Dougal Maclaurin (FHPNC@ICFP, 2021)

Decomposing reverse-mode automatic differentiation. - Roy Frostig; Matthew J. Johnson 002; Dougal Maclaurin; Adam Paszke; Alexey Radul (CoRR, 2021)

Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. - Xuesu Xiao; Tingnan Zhang; Krzysztof Marcin Choromanski; Tsang-Wei Edward Lee; Anthony G. Francis; Jake Varley; Stephen Tu; Sumeet Singh; Peng Xu 010; Fei Xia 002; Sven Mikael Persson; Dmitry Kalashnikov; et al. (CoRL, 2022)

Efficient and Modular Implicit Differentiation. - Mathieu Blondel; Quentin Berthet; Marco Cuturi; Roy Frostig; Stephan Hoyer; Felipe Llinares-López; Fabian Pedregosa; Jean-Philippe Vert (NeurIPS, 2022)

You Only Linearize Once: Tangents Transpose to Gradients. - Alexey Radul; Adam Paszke; Roy Frostig; Matthew J. Johnson 002; Dougal Maclaurin (Proc. ACM Program. Lang., 2023)

Learning from many trajectories. - Stephen Tu; Roy Frostig; Mahdi Soltanolkotabi (J. Mach. Learn. Res., 2024)