3 citations · 6 across the 8 of their papers we have counts for
8 papers
Optimizing Shortfall Risk Metric for Learning Regression Models
Harish G. Ramaswamy, L. A. Prashanth
We consider the problem of estimating and optimizing utility-based shortfall risk (UBSR) of a loss, say , in the context of a regression problem. Empirical risk min…
Generalized Simultaneous Perturbation-based Gradient Search with Reduced Estimator Bias
Soumen Pachal, Shalabh Bhatnagar, L. A. Prashanth
We present in this paper a family of generalized simultaneous perturbation-based gradient search (GSPGS) estimators that use noisy function measurements. The number of function mea…
Minimum mean-squared error estimation with bandit feedback
Ayon Ghosh, L. A. Prashanth, Dipayan Sen +1
We consider the problem of sequentially learning to estimate, in the mean squared error (MSE) sense, a Gaussian -vector of unknown covariance by observing only of its en…
Simultaneous Perturbation Algorithms for Batch Off-Policy Search
Raphael Fonteneau, L. A. Prashanth
We propose novel policy search algorithms in the context of off-policy, batch mode reinforcement learning (RL) with continuous state and action spaces. Given a batch collection of…
Variance-Constrained Actor-Critic Algorithms for Discounted and Average Reward MDPs
Prashanth L. A., Mohammad Ghavamzadeh
In many sequential decision-making problems we may want to manage risk by minimizing some measure of variability in rewards in addition to maximizing a standard criterion. Variance…
Simultaneous Perturbation Methods for Adaptive Labor Staffing in Service Systems
L. A. Prashanth, H. L. Prasad, Nirmit Desai +2
Service systems are labor intensive due to the large variation in the tasks required to address service requests from multiple customers. Aligning the staffing levels to the foreca…
Two Timescale Convergent Q-learning for Sleep--Scheduling in Wireless Sensor Networks
Prashanth L. A., Abhranil Chatterjee, Shalabh Bhatnagar
In this paper, we consider an intrusion detection application for Wireless Sensor Networks (WSNs). We study the problem of scheduling the sleep times of the individual sensors to m…
Concentration bounds for temporal difference learning with linear function approximation: The case of batch data and uniform sampling
L. A. Prashanth, Nathaniel Korda, Rémi Munos
We propose a stochastic approximation (SA) based method with randomization of samples for policy evaluation using the least squares temporal difference (LSTD) algorithm. Our propos…