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L A Prashanth
Associate Professor
Email : prashla [at] cse [dot] iitm [dot] ac [dot] in | Phone : (+91)-44-2257-4377
Lab(s) : RL.
Link to Personal Homepage
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Research Interests :
Reinforcement Learning, Stochastic Optimization, Multi-armed Bandits.Publications : (Last Five, while at IITM)DBLP | View All
- Policy Evaluation for Variance in Average Reward Reinforcement Learning.
Authors :
Shubhada Agrawal,
L A Prashanth,
Siva Theja MaguluriAppeared in
Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024 (ICML 2024) ,Vol , No., Jul 2024
- Risk Estimation in a Markov Cost Process: Lower and Upper Bounds.
Authors :
Gugan Thoppe,
L A Prashanth,
Sanjay P. BhatAppeared in
Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024 (ICML 2024) ,Vol , No., Jul 2024
- A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning.
Authors :
Mizhaan Prajit Maniyar,
L A Prashanth,
Akash Mondal,
Shalabh BhatnagarAppeared 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.
Authors :
Akash Mondal,
L A Prashanth,
Shalabh BhatnagarAppeared in
Autom., Vol 162, No., pp.111528, Jan 2024
- A policy gradient approach for optimization of smooth risk measures.
Authors :
Nithia Vijayan,
L A PrashanthAppeared in
Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA. (UAI 2023) ,Proceedings of Machine Learning Research, Vol 216, pp.2168-2178, Aug 2023
| Jul 2023 - Nov 2023 | : | - Operating Systems (CS3500) |
| Jan 2023 - May 2023 | : | - Stochastic Optimization (CS6515) |
| Jul 2022 - Nov 2022 | : | - Programming and Data Structures (CS2700) |
| Jan 2022 - Apr 2022 | : | - Object Oriented Algorithms Implementation and Analysis Lab (CS2810) |
| Jan 2022 - Apr 2022 | : | - Topics in Reinforcement Learning (CS7011) |
