Sriram Ganapathi Subramanian

33 papers A* 3A 6Journal 21Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	World of Workflows: a Benchmark for Bringing World Models to Enterprise Systems. CoRR Lakshya Gupta, Litao Li, Yizhe Liu, Sriram Ganapathi Subramanian, Kaheer Suleman, Zichen Zhang, Haoye Lu, Sumit Pasupalak
2025	J	`jnl`	A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges. Trans. Mach. Learn. Res. Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart
2025	A	`conf`	Learning to Negotiate via Voluntary Commitment. AISTATS Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart
2025	J	`jnl`	Learning to Negotiate via Voluntary Commitment. CoRR Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart
2025	J	`jnl`	Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling. CoRR Gustavo Sutter, Mohammed Abdulrahman, Hao Wang, Sriram Ganapathi Subramanian, Marc St-Aubin, Sharon O'Sullivan, Lawrence Wan, Luis A. Ricardez-Sandoval, Pascal Poupart, Agustinus Kristiadi
2024	J	`jnl`	A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges. CoRR Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart
2024	A*	`conf`	Confidence Aware Inverse Constrained Reinforcement Learning. ICML Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart
2024	J	`jnl`	Confidence Aware Inverse Constrained Reinforcement Learning. CoRR Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart
2024	J	`jnl`	How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization? CoRR Agustinus Kristiadi, Felix Strieth-Kalthoff, Sriram Ganapathi Subramanian, Vincent Fortuin, Pascal Poupart, Geoff Pleiss
2023	J	`jnl`	ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry. CoRR Chris Beeler, Sriram Ganapathi Subramanian, Kyle Sprague, Nouha Chatti, Colin Bellinger, Mitchell Shahen, Nicholas Paquin, Mark Baula, Amanuel Dawit, Zihan Yang, Xinkai Li, Mark Crowley, Isaac Tamblyn
2023	A	`conf`	Learning from Multiple Independent Advisors in Multi-agent Reinforcement Learning. AAMAS Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley
2023	J	`jnl`	Learning from Multiple Independent Advisors in Multi-agent Reinforcement Learning. CoRR Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley
2023	A*	`conf`	Multi-Agent Advisor Q-Learning (Extended Abstract). IJCAI Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley
2023	A	`conf`	Two-Level Actor-Critic Using Multiple Teachers. AAMAS Su Zhang, Srijita Das, Sriram Ganapathi Subramanian, Matthew E. Taylor
2023	J	`jnl`	Two-Level Actor-Critic Using Multiple Teachers. Trans. Mach. Learn. Res. Su Zhang, Srijita Das, Sriram Ganapathi Subramanian, Matthew E. Taylor
2022	A*	`conf`	Decentralized Mean Field Games. AAAI Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart
2022	J	`jnl`	Investigation of independent reinforcement learning algorithms in multi-agent environments. Frontiers Artif. Intell. Ken Ming Lee, Sriram Ganapathi Subramanian, Mark Crowley
2022	J	`jnl`	Multi-Agent Advisor Q-Learning. J. Artif. Intell. Res. Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley
2021	J	`jnl`	Decentralized Mean Field Games. CoRR Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart
2021	J	`jnl`	Investigation of Independent Reinforcement Learning Algorithms in Multi-Agent Environments. CoRR Ken Ming Lee, Sriram Ganapathi Subramanian, Mark Crowley
2021	J	`jnl`	Multi-Agent Advisor Q-Learning. CoRR Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley
2021	A	`conf`	Partially Observable Mean Field Reinforcement Learning. AAMAS Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart
2021	J	`jnl`	The Effect of Q-function Reuse on the Total Regret of Tabular, Model-Free, Reinforcement Learning. CoRR Volodymyr Tkachuk, Sriram Ganapathi Subramanian, Matthew E. Taylor
2020	J	`jnl`	A review of machine learning applications in wildfire science and management. CoRR Piyush Jain, Sean C. P. Coogan, Sriram Ganapathi Subramanian, Mark Crowley, Steve Taylor, Mike D. Flannigan
2020	—	`conf`	Deep Multi Agent Reinforcement Learning for Autonomous Driving. Canadian AI Sushrut Bhalla, Sriram Ganapathi Subramanian, Mark Crowley
2020	J	`jnl`	Maximum Reward Formulation In Reinforcement Learning. CoRR Sai Krishna Gottipati, Yashaswi Pathak, Rohan Nuttall, Sahir, Raviteja Chunduru, Ahmed Touati, Sriram Ganapathi Subramanian, Matthew E. Taylor, Sarath Chandar
2020	A	`conf`	Multi Type Mean Field Reinforcement Learning. AAMAS Sriram Ganapathi Subramanian, Pascal Poupart, Matthew E. Taylor, Nidhi Hegde
2020	J	`jnl`	Multi Type Mean Field Reinforcement Learning. CoRR Sriram Ganapathi Subramanian, Pascal Poupart, Matthew E. Taylor, Nidhi Hegde
2020	J	`jnl`	Partially Observable Mean Field Reinforcement Learning. CoRR Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart
2019	A	`conf`	Training Cooperative Agents for Multi-Agent Reinforcement Learning. AAMAS Sushrut Bhalla, Sriram Ganapathi Subramanian, Mark Crowley
2018	—	`conf`	Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Settings. Canadian AI Sriram Ganapathi Subramanian, Mark Crowley
2018	—	`conf`	Decision Assist for Self-driving Cars. Canadian AI Sriram Ganapathi Subramanian, Jaspreet Singh Sambee, Benyamin Ghojogh, Mark Crowley
2018	J	`jnl`	Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models From Satellite Images. Frontiers ICT Sriram Ganapathi Subramanian, Mark Crowley