| Recent Publications | - Policy Evaluation for Variance in Average Reward Reinforcement Learning.
Shubhada Agrawal , L A Prashanth , Siva Theja Maguluri
Appeared in Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024,
Vol , No., Jul 2024 - Risk Estimation in a Markov Cost Process: Lower and Upper Bounds.
Gugan Thoppe , L A Prashanth , Sanjay P. Bhat
Appeared in Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024,
Vol , No., Jul 2024 - A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning.
Mizhaan Prajit Maniyar , L A Prashanth , Akash Mondal , Shalabh Bhatnagar
Appeared in International Conference on Artificial Intelligence and Statistics, 2-4 May 2024, Palau de Congressos, Valencia, Spain.,
Proceedings of Machine Learning Research, Vol 238, pp.4708-4716, May 2024 - Truncated Cauchy random perturbations for smoothed functional-based stochastic optimization.
Akash Mondal , L A Prashanth , Shalabh Bhatnagar
Appeared in Autom.,
Vol 162, No., pp.111528, Jan 2024 - A policy gradient approach for optimization of smooth risk measures.
Nithia Vijayan , L A Prashanth
Appeared in Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA.,
Proceedings of Machine Learning Research, Vol 216, pp.2168-2178, Aug 2023
|
