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03/28/2023
Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise
In this work, we study the concentration behavior of a stochastic approx...
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12/29/2022
Backward Curriculum Reinforcement Learning
The current reinforcement learning algorithm uses forward-generated traj...
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09/25/2022
Matching Queues with Abandonments in Quantum Switches: Stability and Throughput Analysis
Inspired by quantum switches, we consider a discrete-time multi-way matc...
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08/05/2022
Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function Approximation
In this work, we study policy-based methods for solving the reinforcemen...
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06/21/2022
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling
Since reinforcement learning algorithms are notoriously data-intensive, ...
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03/05/2022
Target Network and Truncation Overcome The Deadly triad in Q-Learning
Q-learning with function approximation is one of the most empirically su...
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11/11/2021
Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization
Stochastic approximation (SA) and stochastic gradient descent (SGD) algo...
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08/11/2021
Transportation Polytope and its Applications in Parallel Server Systems
Parallel server system is a stochastic processing network widely studied...
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06/24/2021
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators
In temporal difference (TD) learning, off-policy sampling is known to be...
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05/26/2021
Finite-Sample Analysis of Off-Policy Natural Actor-Critic with Linear Function Approximation
In this paper, we develop a novel variant of off-policy natural actor-cr...
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05/05/2021
Optimal Pricing in Multi Server Systems
We study optimal service pricing in server farms where customers arrive ...
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05/04/2021
On the Linear convergence of Natural Policy Gradient Algorithm
Markov Decision Processes are classically solved using Value Iteration a...
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02/18/2021
Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm
In this paper, we provide finite-sample convergence guarantees for an of...
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02/02/2021
A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants
This paper develops an unified framework to study finite-sample converge...
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01/26/2021
Finite Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm
Actor-critic style two-time-scale algorithms are very popular in reinfor...
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04/26/2020
Low-Complexity Switch Scheduling Algorithms: Delay Optimality in Heavy Traffic
Motivated by applications in data center networks, in this paper, we stu...
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02/03/2020
Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes
Stochastic Approximation (SA) is a popular approach for solving fixed po...
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12/12/2019
Throughput Optimal Routing in Blockchain Based Payment Systems
Cryptocurrency networks such as Bitcoin have emerged as a distributed al...
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07/25/2019
Finite-Time Performance of Distributed Temporal Difference Learning with Linear Function Approximation
We study the policy evaluation problem in multi-agent reinforcement lear...
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05/27/2019
Finite-Time Analysis of Q-Learning with Linear Function Approximation
In this paper, we consider the model-free reinforcement learning problem...
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05/14/2019
QPS-r: A Cost-Effective Crossbar Scheduling Algorithm and Its Stability and Delay Analysis
Parallel iterative maximal matching algorithms (adapted for switching) h...
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08/06/2018
Heavy-Traffic Insensitive Bounds for Weighted Proportionally Fair Bandwidth Sharing Policies
We consider a connection-level model proposed by Massoulié and Roberts f...
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11/02/2016