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ORCIDNir Levine
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2020 – today
- 2024
[i12]Irina Jurenka, Markus Kunesch, Kevin R. McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine L. Hermann, Daniel Kasenberg, Avishkar Bhoopchand, Ankit Anand, Miruna Pîslar, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulous, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim:
Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. CoRR abs/2407.12687 (2024)- 2021
- [j1]Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester:
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. Mach. Learn. 110(9): 2419-2468 (2021) - [c8]Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann:
Balancing Constraints and Rewards with Meta-Gradient D4PG. ICLR 2021 - [i11]Polina Kirichenko, Mehrdad Farajtabar, Dushyant Rao, Balaji Lakshminarayanan, Nir Levine, Ang Li, Huiyi Hu, Andrew Gordon Wilson, Razvan Pascanu:
Task-agnostic Continual Learning with Hybrid Probabilistic Models. CoRR abs/2106.12772 (2021) - 2020
- [c7]Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa, Hassan Ghasemzadeh:
Improved Knowledge Distillation via Teacher Assistant. AAAI 2020: 5191-5198 - [c6]Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui:
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. ICLR 2020 - [c5]Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller:
Robust Reinforcement Learning for Continuous Control with Model Misspecification. ICLR 2020 - [c4]Nevena Lazic, Dong Yin, Mehrdad Farajtabar, Nir Levine, Dilan Görür, Chris Harris, Dale Schuurmans:
A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs. NeurIPS 2020 - [i10]Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester:
An empirical investigation of the challenges of real-world reinforcement learning. CoRR abs/2003.11881 (2020) - [i9]Nevena Lazic, Dong Yin, Mehrdad Farajtabar, Nir Levine, Dilan Görür, Chris Harris, Dale Schuurmans:
A maximum-entropy approach to off-policy evaluation in average-reward MDPs. CoRR abs/2006.12620 (2020) - [i8]Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann:
Balancing Constraints and Rewards with Meta-Gradient D4PG. CoRR abs/2010.06324 (2020) - [i7]Hongzi Mao, Chenjie Gu, Miaosen Wang, Angie Chen, Nevena Lazic, Nir Levine, Derek Pang, Rene Claus, Marisabel Hechtman, Ching-Han Chiang, Cheng Chen, Jingning Han:
Neural Rate Control for Video Encoding using Imitation Learning. CoRR abs/2012.05339 (2020)
2010 – 2019
- 2019
- [i6]Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy A. Mann, Todd Hester, Martin A. Riedmiller:
Robust Reinforcement Learning for Continuous Control with Model Misspecification. CoRR abs/1906.07516 (2019) - [i5]Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui:
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. CoRR abs/1909.01506 (2019) - 2017
- [c3]Nir Levine, Koby Crammer, Shie Mannor:
Rotting Bandits. NIPS 2017: 3074-3083 - [c2]Nir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor:
Shallow Updates for Deep Reinforcement Learning. NIPS 2017: 3135-3145 - [c1]Nir Levine, Haggai Roitman, Doron Cohen:
An Extended Relevance Model for Session Search. SIGIR 2017: 865-868 - [i4]Nir Levine, Koby Crammer, Shie Mannor:
Rotting Bandits. CoRR abs/1702.07274 (2017) - [i3]Nir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor:
Shallow Updates for Deep Reinforcement Learning. CoRR abs/1705.07461 (2017) - [i2]Nir Levine, Haggai Roitman, Doron Cohen:
An Extended Relevance Model for Session Search. CoRR abs/1706.02061 (2017) - 2015
- [i1]Nir Levine, Timothy A. Mann, Shie Mannor:
Actively Learning to Attract Followers on Twitter. CoRR abs/1504.04114 (2015)
Coauthor Index
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