Actively Learning to Attract Followers on Twitter. - Nir Levine; Timothy A. Mann; Shie Mannor (CoRR, 2015)

Rotting Bandits. - Nir Levine; Koby Crammer; Shie Mannor (NIPS, 2017)

Shallow Updates for Deep Reinforcement Learning. - Nir Levine; Tom Zahavy; Daniel J. Mankowitz; Aviv Tamar; Shie Mannor (NIPS, 2017)

An Extended Relevance Model for Session Search. - Nir Levine; Haggai Roitman; Doron Cohen 001 (SIGIR, 2017)

Robust Reinforcement Learning for Continuous Control with Model Misspecification. - Daniel J. Mankowitz; Nir Levine; Rae Jeong; Abbas Abdolmaleki; Jost Tobias Springenberg; Timothy A. Mann; Todd Hester; Martin A. Riedmiller (CoRR, 2019)

Improved Knowledge Distillation via Teacher Assistant. - Seyed-Iman Mirzadeh; Mehrdad Farajtabar; Ang Li; Nir Levine; Akihiro Matsukawa; Hassan Ghasemzadeh 001 (AAAI, 2020)

Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. - Nir Levine; Yinlam Chow; Rui Shu; Ang Li; Mohammad Ghavamzadeh; Hung Bui (ICLR, 2020)

Robust Reinforcement Learning for Continuous Control with Model Misspecification. - Daniel J. Mankowitz; Nir Levine; Rae Jeong; Abbas Abdolmaleki; Jost Tobias Springenberg; Yuanyuan Shi; Jackie Kay; Todd Hester; Timothy A. Mann; Martin A. Riedmiller (ICLR, 2020)

A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs. - Nevena Lazic; Dong Yin; Mehrdad Farajtabar; Nir Levine; Dilan Görür; Chris Harris 001; Dale Schuurmans (NeurIPS, 2020)

An empirical investigation of the challenges of real-world reinforcement learning. - Gabriel Dulac-Arnold; Nir Levine; Daniel J. Mankowitz; Jerry Li; Cosmin Paduraru; Sven Gowal; Todd Hester (CoRR, 2020)

Neural Rate Control for Video Encoding using Imitation Learning. - 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 (CoRR, 2020)

Balancing Constraints and Rewards with Meta-Gradient D4PG. - Dan A. Calian; Daniel J. Mankowitz; Tom Zahavy; Zhongwen Xu; Junhyuk Oh; Nir Levine; Timothy A. Mann (ICLR, 2021)

Task-agnostic Continual Learning with Hybrid Probabilistic Models. - Polina Kirichenko; Mehrdad Farajtabar; Dushyant Rao; Balaji Lakshminarayanan; Nir Levine; Ang Li; Huiyi Hu; Andrew Gordon Wilson; Razvan Pascanu (CoRR, 2021)

Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. - Gabriel Dulac-Arnold; Nir Levine; Daniel J. Mankowitz; Jerry Li; Cosmin Paduraru; Sven Gowal; Todd Hester (Mach. Learn., 2021)

Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. - 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; et al. (CoRR, 2024)