| Ray: A distributed framework for emerging {AI} applications P Moritz, R Nishihara, S Wang, A Tumanov, R Liaw, E Liang, M Elibol, ... 13th USENIX symposium on operating systems design and implementation (OSDI …, 2018 | 1317 | 2018 |
| RLlib: Abstractions for distributed reinforcement learning E Liang, R Liaw, R Nishihara, P Moritz, R Fox, K Goldberg, J Gonzalez, ... International conference on machine learning, 3053-3062, 2018 | 1104* | 2018 |
| Tune: A research platform for distributed model selection and training R Liaw, E Liang, R Nishihara, P Moritz, JE Gonzalez, I Stoica arXiv preprint arXiv:1807.05118, 2018 | 984 | 2018 |
| A general analysis of the convergence of ADMM R Nishihara, L Lessard, B Recht, A Packard, M Jordan International conference on machine learning, 343-352, 2015 | 356 | 2015 |
| A linearly-convergent stochastic L-BFGS algorithm P Moritz, R Nishihara, M Jordan Artificial Intelligence and Statistics, 249-258, 2016 | 292 | 2016 |
| Discovering causal signals in images D Lopez-Paz, R Nishihara, S Chintala, B Scholkopf, L Bottou Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 257 | 2017 |
| Sparknet: Training deep networks in spark P Moritz, R Nishihara, I Stoica, MI Jordan arXiv preprint arXiv:1511.06051, 2015 | 224 | 2015 |
| Parallel MCMC with generalized elliptical slice sampling R Nishihara, I Murray, RP Adams The Journal of Machine Learning Research 15 (1), 2087-2112, 2014 | 95 | 2014 |
| Real-time machine learning: The missing pieces R Nishihara, P Moritz, S Wang, A Tumanov, W Paul, J Schleier-Smith, ... Proceedings of the 16th workshop on hot topics in operating systems, 106-110, 2017 | 81 | 2017 |
| On the convergence rate of decomposable submodular function minimization R Nishihara, S Jegelka, MI Jordan Advances in Neural Information Processing Systems 27, 2014 | 51 | 2014 |
| Lineage stash: fault tolerance off the critical path S Wang, J Liagouris, R Nishihara, P Moritz, U Misra, A Tumanov, I Stoica Proceedings of the 27th ACM Symposium on Operating Systems Principles, 338-352, 2019 | 48 | 2019 |
| Policy gradient search: Online planning and expert iteration without search trees T Anthony, R Nishihara, P Moritz, T Salimans, J Schulman arXiv preprint arXiv:1904.03646, 2019 | 31 | 2019 |
| Hoplite: efficient and fault-tolerant collective communication for task-based distributed systems S Zhuang, Z Li, D Zhuo, S Wang, E Liang, R Nishihara, P Moritz, I Stoica Proceedings of the 2021 ACM SIGCOMM 2021 Conference, 641-656, 2021 | 24 | 2021 |
| Detecting parameter symmetries in probabilistic models R Nishihara, T Minka, D Tarlow arXiv preprint arXiv:1312.5386, 2013 | 18 | 2013 |
| No regret bound for extreme bandits R Nishihara, D Lopez-Paz, L Bottou Artificial Intelligence and Statistics, 259-267, 2016 | 12 | 2016 |
| ESCHER: expressive scheduling with ephemeral resources R Bhardwaj, A Tumanov, S Wang, R Liaw, P Moritz, R Nishihara, I Stoica Proceedings of the 13th Symposium on Cloud Computing, 47-62, 2022 | 4 | 2022 |
| Flexible Primitives for Distributed Deep Learning in Ray Y Bulatov, R Nishihara, P Moritz, M Elibol, I Stoica, MI Jordan SysML Conference, 2018 | 1 | 2018 |
| On Systems and Algorithms for Distributed Machine Learning R Nishihara UC Berkeley, 2019 | | 2019 |
Philipp MoritzGraduate Student, UC Berkeley在 berkeley.edu 的电子邮件经过验证
