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Articles by Sean Meyn

The ODE Method for Asymptotic Statistics in Stochastic Approximation and Reinforcement Learning
15 November 2024 by Vivek Borkar and others
Statistics Theory, Machine Learning
Reinforcement Learning Design for Quickest Change Detection
13 September 2024 by Austin Cooper and Sean Meyn at LogoUniversity of Florida
Optimization and Control, Information Theory
Quickest Change Detection Using Mismatched CUSUM
12 September 2024 by Austin Cooper and Sean Meyn
Statistics Theory, Information Theory
Markovian Foundations for Quasi-Stochastic Approximation in Two Timescales: Extended Version
12 September 2024 by Caio Kalil Lauand and Sean Meyn
Optimization and Control
Lecture Notes on Control System Theory and Design
11 July 2024 by Tamer Başar and others
Optimization and Control, Systems and Control
Revisiting Step-Size Assumptions in Stochastic Approximation
3 June 2024 by Caio Kalil Lauand and Sean Meyn
Statistics Theory, Machine Learning
Markovian Foundations for Quasi-Stochastic Approximation with Applications to Extremum Seeking Control
1 April 2024 by Caio Kalil Lauand and Sean Meyn
Optimization and Control
Extremely Fast Convergence Rates for Extremum Seeking Control with Polyak-Ruppert Averaging
25 March 2024 by Caio Kalil Lauand and Sean Meyn
Optimization and Control
The Curse of Memory in Stochastic Approximation: Extended Version
17 September 2023 by Caio Kalil Lauand and Sean Meyn
Statistics Theory, Machine Learning
Convex Q Learning in a Stochastic Environment: Extended Version
10 September 2023 by Fan Lu and Sean Meyn
Optimization and Control, Machine Learning
Stability of Q-Learning Through Design and Optimism
21 August 2023 by Sean Meyn
Machine Learning, Systems and Control
High-Impedance Non-Linear Fault Detection via Eigenvalue Analysis with low PMU Sampling Rates
10 January 2023 by Gian Paramo and others
Systems and Control
High Impedance Fault Detection Through Quasi-Static State Estimation: A Parameter Error Modeling Approach
20 December 2022 by Austin Cooper and others
Systems and Control
Uncertainty Error Modeling for Non-Linear State Estimation With Unsynchronized SCADA and μPMU Measurements
20 December 2022 by Austin Cooper and others
Systems and Control
Sufficient Exploration for Convex Q-learning
17 October 2022 by Fan Lu and others
Optimization and Control, Machine Learning
Model-Free Characterizations of the Hamilton-Jacobi-Bellman Equation and Convex Q-Learning in Continuous Time
14 October 2022 by Fan Lu and others
Optimization and Control, Machine Learning
Feature Projection for Optimal Transport
3 August 2022 by Thibault Corre and others at LogoUniversity of Florida
Optimization and Control
The Conditional Poincaré Inequality for Filter Stability
8 October 2021 by Jin Won Kim and others
Probability, Optimization and Control
Kullback-Leibler-Quadratic Optimal Control
16 July 2021 by Neil Cammardella and others
Optimization and Control
Reliable Power Grid: Long Overdue Alternatives to Surge Pricing
26 March 2021 by Hala Ballouz and others
Optimization and Control, Systems and Control
Aggregate capacity of TCLs with cycling constraints
13 October 2020 by Austin Coffman and others at LogoUniversity of Florida
Systems and Control
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation
1 October 2020 by Shuhang Chen and others
Optimization and Control, Machine Learning
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation
7 February 2020 by Shuhang Chen and others
Probability, Machine Learning
Demand Dispatch with Heterogeneous Intelligent Loads
24 October 2019 by Joel Mathias and others
Systems and Control, Optimization and Control
Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow
28 September 2019 by Yue Chen and others
Optimization and Control, Systems and Control
State Space Collapse in Resource Allocation for Demand Dispatch
15 September 2019 by Joel Mathias and others at LogoUniversity of Florida
Systems and Control, Optimization and Control
Diffusion approximations and control variates for MCMC
8 July 2019 by Nicolas Brosse and others
Methodology
Optimal Rate of Convergence for Quasi-Stochastic Approximation
18 March 2019 by Andrey Bernstein and others
Optimization and Control
Optimal Matrix Momentum Stochastic Approximation and Applications to Q-learning
5 February 2019 by Adithya Devraj and others
Optimization and Control, Machine Learning
Action-Constrained Markov Decision Processes With Kullback-Leibler Cost
26 July 2018 by Ana Busic and Sean Meyn
Optimization and Control
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