| JAX: composable transformations of Python + NumPy programs J Bradbury, R Frostig, P Hawkins, MJ Johnson, C Leary, D Maclaurin, ... URL http://github.com/google/jax, 2018 | 2954 | 2018 |
| Semantic Parsing on Freebase from Question-Answer Pairs J Berant, A Chou, R Frostig, P Liang Empirical methods in natural language processing (EMNLP), 2013 | 2294 | 2013 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 671* | 2024 |
| Measuring the Effects of Data Parallelism on Neural Network Training CJ Shallue, J Lee, J Antognini, J Sohl-Dickstein, R Frostig, GE Dahl Journal of Machine Learning Research 20 (112), 1-49, 2019 | 446 | 2019 |
| Toward deeper understanding of neural networks: The power of initialization and a dual view on expressivity A Daniely, R Frostig, Y Singer Advances In Neural Information Processing Systems 29, 2016 | 392 | 2016 |
| Compiling machine learning programs via high-level tracing R Frostig, MJ Johnson, C Leary SysML, 2018 | 351 | 2018 |
| Efficient and modular implicit differentiation M Blondel, Q Berthet, M Cuturi, R Frostig, S Hoyer, F Llinares-López, ... Advances in Neural Information Processing Systems 35, 5230-5242, 2022 | 259 | 2022 |
| Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization R Frostig, R Ge, SM Kakade, A Sidford Proceedings of The 32nd International Conference on Machine Learning, 2540-2548, 2015 | 174 | 2015 |
| Competing with the empirical risk minimizer in a single pass R Frostig, R Ge, SM Kakade, A Sidford Conference on learning theory, 728-763, 2015 | 130 | 2015 |
| Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation X Xiao, T Zhang, K Choromanski, E Lee, A Francis, J Varley, S Tu, ... arXiv preprint arXiv:2209.10780, 2022 | 45 | 2022 |
| Principal component projection without principal component analysis R Frostig, C Musco, C Musco, A Sidford International Conference on Machine Learning, 2349-2357, 2016 | 38 | 2016 |
| The advantages of multiple classes for reducing overfitting from test set reuse V Feldman, R Frostig, M Hardt International Conference on Machine Learning, 1892-1900, 2019 | 36 | 2019 |
| Learning from many trajectories S Tu, R Frostig, M Soltanolkotabi Journal of Machine Learning Research 25 (216), 1-109, 2024 | 28 | 2024 |
| You Only Linearize Once: Tangents Transpose to Gradients A Radul, A Paszke, R Frostig, MJ Johnson, D Maclaurin Proceedings of the ACM on Programming Languages 7 (POPL), 1246-1274, 2023 | 25 | 2023 |
| Simple MAP inference via low-rank relaxations R Frostig, S Wang, PS Liang, CD Manning Advances in Neural Information Processing Systems 27, 2014 | 21 | 2014 |
| Random Features for Compositional Kernels A Daniely, R Frostig, V Gupta, Y Singer arXiv preprint arXiv:1703.07872, 2017 | 15 | 2017 |
| Estimation from Indirect Supervision with Linear Moments A Raghunathan, R Frostig, J Duchi, P Liang arXiv preprint arXiv:1608.03100, 2016 | 15 | 2016 |
| Decomposing reverse-mode automatic differentiation R Frostig, MJ Johnson, D Maclaurin, A Paszke, A Radul arXiv preprint arXiv:2105.09469, 2021 | 12 | 2021 |
| Parallelism-preserving automatic differentiation for second-order array languages A Paszke, MJ Johnson, R Frostig, D Maclaurin Proceedings of the 9th ACM SIGPLAN International Workshop on Functional High …, 2021 | 7 | 2021 |
| Relaxations for inference in restricted Boltzmann machines SI Wang, R Frostig, P Liang, CD Manning arXiv preprint arXiv:1312.6205, 2013 | 7 | 2013 |
Percy LiangAssociate Professor of Computer Science, Stanford UniversityZweryfikowany adres z cs.stanford.edu
