4 papers
Self-Interested Agents in Collaborative Machine Learning: An Incentivized Adaptive Data-Centric Framework
Nithia Vijayan, Bryan Kian Hsiang Low
We propose a framework for adaptive data-centric collaborative machine learning among self-interested agents, coordinated by an arbiter. Designed to handle the incremental nature o…
A policy gradient approach for optimization of smooth risk measures
Nithia Vijayan, Prashanth L. A
We propose policy gradient algorithms for solving a risk-sensitive reinforcement learning (RL) problem in on-policy as well as off-policy settings. We consider episodic Markov deci…
Policy Gradient Methods for Distortion Risk Measures
Nithia Vijayan, Prashanth L. A
We propose policy gradient algorithms which learn risk-sensitive policies in a reinforcement learning (RL) framework. Our proposed algorithms maximize the distortion risk measure (…
Smoothed functional-based gradient algorithms for off-policy reinforcement learning: A non-asymptotic viewpoint
Nithia Vijayan, Prashanth L. A
We propose two policy gradient algorithms for solving the problem of control in an off-policy reinforcement learning (RL) context. Both algorithms incorporate a smoothed functional…