19 citations · 48 across the 9 of their papers we have counts for
10 papers
Online Learning for Cooperative Multi-Player Multi-Armed Bandits
William Chang, Mehdi Jafarnia-Jahromi, Rahul Jain
We introduce a framework for decentralized online learning for multi-armed bandits (MAB) with multiple cooperative players. The reward obtained by the players in each round depends…
A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent
Mehdi Jafarnia-Jahromi, Rahul Jain, Ashutosh Nayyar
In this paper, we propose Posterior Sampling Reinforcement Learning for Zero-sum Stochastic Games (PSRL-ZSG), the first online learning algorithm that achieves Bayesian regret boun…
Online Learning for Stochastic Shortest Path Model via Posterior Sampling
Mehdi Jafarnia-Jahromi, Liyu Chen, Rahul Jain +1
We consider the problem of online reinforcement learning for the Stochastic Shortest Path (SSP) problem modeled as an unknown MDP with an absorbing state. We propose PSRL-SSP, a si…
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path
Liyu Chen, Mehdi Jafarnia-Jahromi, Rahul Jain +1
We introduce a generic template for developing regret minimization algorithms in the Stochastic Shortest Path (SSP) model, which achieves minimax optimal regret as long as certain…
Online Learning for Unknown Partially Observable MDPs
Mehdi Jafarnia-Jahromi, Rahul Jain, Ashutosh Nayyar
Solving Partially Observable Markov Decision Processes (POMDPs) is hard. Learning optimal controllers for POMDPs when the model is unknown is harder. Online learning of optimal con…
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo +1
We develop several new algorithms for learning Markov Decision Processes in an infinite-horizon average-reward setting with linear function approximation. Using the optimism princi…
A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret
Mehdi Jafarnia-Jahromi, Chen-Yu Wei, Rahul Jain +1
Recently, model-free reinforcement learning has attracted research attention due to its simplicity, memory and computation efficiency, and the flexibility to combine with function…
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo +2
Model-free reinforcement learning is known to be memory and computation efficient and more amendable to large scale problems. In this paper, two model-free algorithms are introduce…
PPD: Permutation Phase Defense Against Adversarial Examples in Deep Learning
Mehdi Jafarnia-Jahromi, Tasmin Chowdhury, Hsin-Tai Wu +1
Deep neural networks have demonstrated cutting edge performance on various tasks including classification. However, it is well known that adversarially designed imperceptible pertu…
Non-indexability of the Stochastic Appointment Scheduling Problem
Mehdi Jafarnia-Jahromi, Rahul Jain
Consider a set of jobs with independent random service times to be scheduled on a single machine. The jobs can be surgeries in an operating room, patients' appointments in outpatie…