Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 2183 | 2023 |
Improved knowledge distillation via teacher assistant SI Mirzadeh, M Farajtabar, A Li, N Levine, A Matsukawa, H Ghasemzadeh Proceedings of the AAAI conference on artificial intelligence 34 (04), 5191-5198, 2020 | 1273 | 2020 |
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 | 684 | 2024 |
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis G Dulac-Arnold, N Levine, DJ Mankowitz, J Li, C Paduraru, S Gowal, ... Machine Learning 110 (9), 2419-2468, 2021 | 531 | 2021 |
An empirical investigation of the challenges of real-world reinforcement learning G Dulac-Arnold, N Levine, DJ Mankowitz, J Li, C Paduraru, S Gowal, ... arXiv preprint arXiv:2003.11881, 2020 | 146 | 2020 |
Rotting bandits N Levine, K Crammer, S Mannor Advances in neural information processing systems 30, 2017 | 140 | 2017 |
Robust reinforcement learning for continuous control with model misspecification DJ Mankowitz, N Levine, R Jeong, Y Shi, J Kay, A Abdolmaleki, ... arXiv preprint arXiv:1906.07516, 2019 | 130 | 2019 |
Shallow updates for deep reinforcement learning N Levine, T Zahavy, DJ Mankowitz, A Tamar, S Mannor Advances in Neural Information Processing Systems 30, 2017 | 51 | 2017 |
Prediction, consistency, curvature: Representation learning for locally-linear control N Levine, Y Chow, R Shu, A Li, M Ghavamzadeh, H Bui arXiv preprint arXiv:1909.01506, 2019 | 34 | 2019 |
Optimization and generalization of regularization-based continual learning: a loss approximation viewpoint D Yin, M Farajtabar, A Li, N Levine, A Mott arXiv preprint arXiv:2006.10974, 2020 | 29 | 2020 |
Balancing constraints and rewards with meta-gradient d4pg DA Calian, DJ Mankowitz, T Zahavy, Z Xu, J Oh, N Levine, T Mann International Conference on Learning Representations, 2020 | 25 | 2020 |
An extended relevance model for session search N Levine, H Roitman, D Cohen Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017 | 21 | 2017 |
Task-agnostic continual learning with hybrid probabilistic models P Kirichenko, M Farajtabar, D Rao, B Lakshminarayanan, N Levine, A Li, ... arXiv preprint arXiv:2106.12772, 2021 | 20 | 2021 |
Towards responsible development of generative AI for education: An evaluation-driven approach I Jurenka, M Kunesch, KR McKee, D Gillick, S Zhu, S Wiltberger, SM Phal, ... arXiv preprint arXiv:2407.12687, 2024 | 16 | 2024 |
A maximum-entropy approach to off-policy evaluation in average-reward mdps N Lazic, D Yin, M Farajtabar, N Levine, D Gorur, C Harris, D Schuurmans Advances in Neural Information Processing Systems 33, 12461-12471, 2020 | 11 | 2020 |
Actively learning to attract followers on Twitter N Levine, TA Mann, S Mannor arXiv preprint arXiv:1504.04114, 2015 | 3 | 2015 |
Robust reinforcement learning for continuous control with model misspecification DJ Mankowitz, N Levine, RC Jeong, A Abdolmaleki, JT Springenberg, ... US Patent App. 17/620,164, 2022 | 2 | 2022 |
Neural Rate Control for Video Encoding using Imitation Learning H Mao, C Gu, M Wang, A Chen, N Lazic, N Levine, D Pang, R Claus, ... arXiv preprint arXiv:2012.05339, 2020 | 1 | 2020 |
Relevance model for session search H Roitman, D Cohen, N Levine US Patent 10,956,409, 2021 | | 2021 |