Identifying User Survival Types via Clustering of Censored Social Network Data. - S. Chandra Mouli; Abhishek Naik; Bruno Ribeiro 001; Jennifer Neville (CoRR, 2017)

RAIL: Risk-Averse Imitation Learning. - Anirban Santara; Abhishek Naik; Balaraman Ravindran; Dipankar Das 002; Dheevatsa Mudigere; Sasikanth Avancha; Bharat Kaul (AAMAS, 2018)

Discounted Reinforcement Learning is Not an Optimization Problem. - Abhishek Naik; Roshan Shariff; Niko Yasui; Richard S. Sutton (CoRR, 2019)

Learning and Planning in Average-Reward Markov Decision Processes. - Yi Wan 004; Abhishek Naik; Richard S. Sutton (ICML, 2021)

Average-Reward Learning and Planning with Options. - Yi Wan 004; Abhishek Naik; Richard S. Sutton (NeurIPS, 2021)

Planning with Expectation Models for Control. - Katya Kudashkina; Yi Wan 004; Abhishek Naik; Richard S. Sutton (CoRR, 2021)

MADRaS : Multi Agent Driving Simulator. - Anirban Santara; Sohan Rudra; Sree Aditya Buridi; Meha Kaushik; Abhishek Naik; Bharat Kaul; Balaraman Ravindran (J. Artif. Intell. Res., 2021)

Recommending Best Quality Image Using Tracking and Re-identification Approaches. - Alim Manjiyani; Abhishek Naik; Swathi Jamjala Narayanan; Boominathan Perumal (ICHSA, 2022)

Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. - Abhishek Naik; Bo Chang 002; Alexandros Karatzoglou; Martin Mladenov; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2023)

Reward Centering. - Abhishek Naik; Yi Wan 004; Manan Tomar; Richard S. Sutton (RLJ, 2024)

Energy-Efficient Satellite IoT Optical Downlinks Using Weather-Adaptive Reinforcement Learning. - Ethan Fettes; Pablo G. Madoery; Halim Yanikomeroglu; Gunes Karabulut-Kurt; Abhishek Naik; Colin Bellinger; Stephane Martel; Khaled Ahmed 005; Sameera Siddiqui (CoRR, 2025)