111 citations · 420 across the 100 of their papers we have counts for
6 papers · 1 filter
Conservative Stochastic Optimization with Expectation Constraints
Zeeshan Akhtar, Amrit Singh Bedi, Ketan Rajawat
This paper considers stochastic convex optimization problems where the objective and constraint functions involve expectations with respect to the data indices or environmental var…
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
Junyu Zhang, Alec Koppel, Amrit Singh Bedi +2
In recent years, reinforcement learning (RL) systems with general goals beyond a cumulative sum of rewards have gained traction, such as in constrained problems, exploration, and a…
Regret and Belief Complexity Trade-off in Gaussian Process Bandits via Information Thresholding
Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal +2
Bayesian optimization is a framework for global search via maximum a posteriori updates rather than simulated annealing, and has gained prominence for decision-making under uncerta…
Asynchronous and Parallel Distributed Pose Graph Optimization
Yulun Tian, Alec Koppel, Amrit Singh Bedi +1
We present Asynchronous Stochastic Parallel Pose Graph Optimization (ASAPP), the first asynchronous algorithm for distributed pose graph optimization (PGO) in multi-robot simultane…
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang +1
We study the estimation of risk-sensitive policies in reinforcement learning problems defined by a Markov Decision Process (MDPs) whose state and action spaces are countably finite…
Online Trajectory Optimization Using Inexact Gradient Feedback for Time-Varying Environments
Mohan Krishna Nutalapati, Amrit Singh Bedi, Ketan Rajawat +1
This paper considers the problem of online trajectory design under time-varying environments. We formulate the general trajectory optimization problem within the framework of time-…