5 citations · 7 across the 18 of their papers we have counts for
4 papers · 1 filter
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning
Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini +1
In this paper, we prove the first Bayesian regret bounds for Thompson Sampling in reinforcement learning in a multitude of settings. We simplify the learning problem using a discre…
Learning-based Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation
Chang-Lin Chen, Hanhan Zhou, Jiayu Chen +8
Online optimization of resource management for large-scale data centers and infrastructures to meet dynamic capacity reservation demands and various practical constraints (e.g., fe…
A Unified Approach for Maximizing Continuous DR-submodular Functions
Mohammad Pedramfar, Christopher John Quinn, Vaneet Aggarwal
This paper presents a unified approach for maximizing continuous DR-submodular functions that encompasses a range of settings and oracle access types. Our approach includes a Frank…
Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback
Mohammad Pedramfar, Vaneet Aggarwal
This paper investigates the problem of combinatorial multiarmed bandits with stochastic submodular (in expectation) rewards and full-bandit delayed feedback, where the delayed feed…