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06/20/2023
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards
In a broad class of reinforcement learning applications, stochastic rewa...
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01/02/2023
Age-Optimal Multi-Channel-Scheduling under Energy and Tolerance Constraints
We study the optimal scheduling problem where n source nodes attempt to ...
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06/09/2021
A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback
In a wide variety of applications including online advertising, contract...
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06/30/2020
Continuous-Time Multi-Armed Bandits with Controlled Restarts
Time-constrained decision processes have been ubiquitous in many fundame...
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06/11/2020
Group-Fair Online Allocation in Continuous Time
The theory of discrete-time online learning has been successfully applie...
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02/29/2020
Budget-Constrained Bandits over General Cost and Reward Distributions
We consider a budget-constrained bandit problem where each arm pull incu...
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12/29/2019
Predictive Scheduling for Virtual Reality
A significant challenge for future virtual reality (VR) applications is ...
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03/24/2019
On the Performance of Mobility-Aware D2D Caching Networks
The increase in demand for spectrum-based services forms a bottleneck in...
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11/27/2018
Optimal Learning for Dynamic Coding in Deadline-Constrained Multi-Channel Networks
We study the problem of serving randomly arriving and delay-sensitive tr...
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06/13/2018
Proactive Resource Allocation with Predictable Channel Statistics
The behavior of users in relatively predictable, both in terms of the da...
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03/11/2018
Combinatorial Multi-Objective Multi-Armed Bandit Problem
In this paper, we introduce the COmbinatorial Multi-Objective Multi-Arme...
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04/26/2017