L.A., Prashanth

8 publications

AISTATS 2024 A Cubic-Regularized Policy Newton Algorithm for Reinforcement Learning Mizhaan P. Maniyar, Prashanth L.A., Akash Mondal, Shalabh Bhatnagar

AISTATS 2023 Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation: Tail Averaging and Regularisation Gandharv Patil, Prashanth L.A., Dheeraj Nagaraj, Doina Precup

JMLR 2022 A Wasserstein Distance Approach for Concentration of Empirical Risk Estimates Prashanth L.A., Sanjay P. Bhat

ICML 2020 Concentration Bounds for CVaR Estimation: The Cases of Light-Tailed and Heavy-Tailed Distributions Prashanth L.A., Krishna Jagannathan, Ravi Kolla

NeurIPS 2019 Concentration of Risk Measures: A Wasserstein Distance Approach Sanjay P. Bhat, Prashanth L.A.

ICML 2019 Correlated Bandits or: How to Minimize Mean-Squared Error Online Vinay Praneeth Boda, Prashanth L.A.

ICML 2016 Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control Prashanth L.A., Cheng Jie, Michael Fu, Steve Marcus, Csaba Szepesvari

NeurIPS 2013 Actor-Critic Algorithms for Risk-Sensitive MDPs Prashanth L.A., Mohammad Ghavamzadeh