6 papers
Optimized Certainty Equivalent Risk Minimization Using Samples: Algorithms, Convergence Rates, and Applications
Sumedh Gupte, Prashanth L. A., Sanjay P. Bhat
We consider the optimization of the Optimized Certainty Equivalent (OCE) risk, with applications including portfolio optimization in finance, and uncertainty quantification, classi…
Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs
Gugan Thoppe, L. A. Prashanth, Ankur Naskar +1
Reinforcement learning (RL) for exponential-utility optimization in discounted Markov decision processes (MDPs) lacks principled value-based algorithms. We address this gap in the…
Reinforcement learning with an expectile-based objective
Sumedh Gupte, Shrey Rakeshkumar Patel, Soumen Pachal +2
We consider the policy evaluation and control in a finite horizon reinforcement learning (RL) setting under an expectile-based objective. First, we derive the mean-squared error (M…
Gradient-based Stochastic Optimization of Utility-based Shortfall Risk
Sumedh Gupte, Prashanth L. A., Sanjay P. Bhat
We consider the problems of estimation and optimization of utility-based shortfall risk (UBSR). We extend UBSR to cover possibly unbounded random variables. We cover prominent risk…
Optimization of utility-based shortfall risk: A non-asymptotic viewpoint
Sumedh Gupte, Prashanth L. A., Sanjay P. Bhat
We consider the problems of estimation and optimization of utility-based shortfall risk (UBSR), which is a popular risk measure in finance. In the context of UBSR estimation, we de…
Risk Estimation in a Markov Cost Process: Lower and Upper Bounds
Gugan Thoppe, L. A. Prashanth, Sanjay Bhat
We tackle the problem of estimating risk measures of the infinite-horizon discounted cost within a Markov cost process. The risk measures we study include variance, Value-at-Risk (…