Upcoming book draft

Gradient-based algorithms for zeroth-order optimization

We shall update this draft frequently over the next few weeks. If you have any comments, or if you find any typos/errors, please email me.

Research Interests

Reinforcement Learning, Zeroth-order Optimization, Multi-armed Bandits

News

Aug-2024: Spending a year at C-MInDS, IITB.
Jun-2024: A paper entitled Optimization of utility-based shortfall risk: A non-asymptotic viewpoint accepted to IEEE Conference on Decision and Control (CDC).
Jun-2024: A paper entitled Online Estimation and Optimization of Utility-Based Shortfall Risk accepted for publication in Mathematics of Operations Research.
May-2024: Two papers accepted to ICML, see here.
Jan-2024: A paper entitled A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning accepted for publication in AISTATS.
Aug-2023: Teaching a course on operating systems. For details, click here.
Jul-2023: Invited talk on ‘Finite time analysis of temporal difference learning with linear function approximation’ at Data science: Probabilistic and optimization methods held at International Centre for Theoretical Sciences, Bengaluru. Click here for the video.
Jan-2023: A paper entitled A policy gradient approach for optimization of smooth risk measures accepted for publication in UAI.
Feb-2023: Invited talk on ‘Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation’ at Networks Seminar Series held (in-person) at Indian Institute of Science. Click here for the video.
Feb-2023: Tutorial on risk-sensitive reinforcement learning at AAAI-2023. Click here for details.
Jan-2023: A paper entitled Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation accepted for publication in AISTATS.
Jan-2023: Teaching a course on stochastic optimization. For details, click here.
Jan-2023: Invited talk on ‘A Wasserstein distance approach for concentration of empirical risk estimates’ at Information Theory and Data Science Workshop held (in-person) at National University of Singapore.
Aug-2022: A paper entitled A Wasserstein distance approach for concentration of empirical risk estimates accepted for publication in Journal of Machine Learning Research.
Jul-2022: Teaching a course on programming and data structures. For details, click here.
Jul-2022: Tutorial on Risk-Aware Multi-armed Bandits at SPCOM 2022. Slides here.
Jun-2022: A monograph entitled Risk-Sensitive Reinforcement Learning via Policy Gradient Search published by Foundations and Trends in Machine Learning.
Apr-2022: A survey article entitled A Survey of Risk-Aware Multi-Armed Bandits accepted at IJCAI-2022.
Feb-2022: Invited talk on ‘Concentration of risk measures: A Wasserstein distance approach’ at ‘IITB Workshop on Stochastic Models’.
Jan-2022: Teaching a course on object oriented analysis using C++. For details, click here.

Prospective interns

I do not have open positions and you are encouraged to apply directly for the IITM summer fellowship programme. Details here