Sean P. Meyn

ORCID

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 86

Top Venues

CoRR

CDC

ACC

IEEE Trans. Autom. Control.

Publications

Anant A. Joshi, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn
Dual Ensemble Kalman Filter for Stochastic Optimal Control. CoRR (2024)
Anant A. Joshi, Heng-Sheng Chang, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn
Design of Interacting Particle Systems for Fast and Efficient Reinforcement Learning. CoRR (2024)
Austin Cooper, Sean P. Meyn
Reinforcement Learning Design for Quickest Change Detection. CoRR (2024)
Mario D. Baquedano-Aguilar, Arturo S. Bretas, Sean P. Meyn, Nader Aljohani
Tri-Level Linear Programming Model for Automatic Load Shedding Using Spectral Clustering. ISGT (2024)
Gian Paramo, Arturo S. Bretas, Sean P. Meyn
Microgrid Frequency Stability: A Proactive Scheme Based on Dynamic Predictions. ISGT (2024)
Joel Mathias, Ana Busic, Sean P. Meyn
Load-Level Control Design for Demand Dispatch With Heterogeneous Flexible Loads. IEEE Trans. Control. Syst. Technol. 31 (4) (2023)
Fan Lu, Sean P. Meyn
Convex Q Learning in a Stochastic Environment: Extended Version. CoRR (2023)
Caio Kalil Lauand, Ana Busic, Sean P. Meyn
Inverse Free Zap Stochastic Approximation Extended Abstract. Allerton (2023)
Fan Lu, Sean P. Meyn
Convex Q Learning in a Stochastic Environment. CDC (2023)
Caio Kalil Lauand, Sean P. Meyn
The Curse of Memory in Stochastic Approximation. CDC (2023)
Ana Busic, Sean P. Meyn, Neil Cammardella
Learning Optimal Policies in Mean Field Models with Kullback-Leibler Regularization. CDC (2023)
Joel Mathias, Sean P. Meyn, Robert Moye, Joseph Warrington
State-Space Collapse in Resource Allocation for Demand Dispatch and Its Implications for Distributed Control Design. IEEE Trans. Autom. Control. 68 (12) (2023)
Neil Cammardella, Ana Busic, Sean P. Meyn
Kullback-Leibler-Quadratic Optimal Control. SIAM J. Control. Optim. 61 (5) (2023)
Fan Lu, Joel Mathias, Sean P. Meyn, Karanjit Kalsi
Convex Q-Learning in Continuous Time with Application to Dispatch of Distributed Energy Resources. CDC (2023)
Sean P. Meyn, Fan Lu, Joel Mathias
Balancing the Power Grid with Cheap Assets. CDC (2023)
Fan Lu, Prashant G. Mehta, Sean P. Meyn, Gergely Neu
Convex Analytic Theory for Convex Q-Learning. CDC (2022)
Joel Mathias, Sean P. Meyn, Hala Ballouz, Meisam Ansari
A Distributed Control Architecture for Optimal Allocation of Grid-responsive Load Aggregations. ISGT (2022)
Fan Lu, Joel Mathias, Sean P. Meyn, Karanjit Kalsi
Model-Free Characterizations of the Hamilton-Jacobi-Bellman Equation and Convex Q-Learning in Continuous Time. CoRR (2022)
Anant A. Joshi, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn
Controlled interacting particle algorithms for simulation-based reinforcement learning. Syst. Control. Lett. 170 (2022)
Caio Kalil Lauand, Sean P. Meyn
Approaching Quartic Convergence Rates for Quasi-Stochastic Approximation with Application to Gradient-Free Optimization. NeurIPS (2022)
Adithya M. Devraj, Sean P. Meyn
Q-Learning With Uniformly Bounded Variance. IEEE Trans. Autom. Control. 67 (11) (2022)
Hala Ballouz, Joel Mathias, Sean P. Meyn, Robert Moye, Joseph Warrington
Reliable Power Grid: Long Overdue Alternatives to Surge Pricing. CoRR (2021)
Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn
Differential Temporal Difference Learning. IEEE Trans. Autom. Control. 66 (10) (2021)
Shuhang Chen, Adithya M. Devraj, Andrey Berstein, Sean P. Meyn
Revisiting the ODE Method for Recursive Algorithms: Fast Convergence Using Quasi Stochastic Approximation. J. Syst. Sci. Complex. 34 (5) (2021)
Fan Lu, Prashant G. Mehta, Sean P. Meyn, Gergely Neu
Convex Q-Learning. ACC (2021)
Shuhang Chen, Adithya M. Devraj, Andrey Bernstein, Sean P. Meyn
Accelerating Optimization and Reinforcement Learning with Quasi Stochastic Approximation. ACC (2021)
Neil Cammardella, Ana Busic, Sean P. Meyn
Kullback-Leibler-Quadratic Optimal Control in a Stochastic Environment. CDC (2021)
Naren Srivaths Raman, Ninad Gaikwad, Prabir Barooah, Sean P. Meyn
Reinforcement Learning-Based Home Energy Management System for Resiliency. ACC (2021)
Vivek S. Borkar, Shuhang Chen, Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn
The ODE Method for Asymptotic Statistics in Stochastic Approximation and Reinforcement Learning. CoRR (2021)
Jin-Won Kim, Prashant G. Mehta, Sean P. Meyn
The Conditional Poincaré Inequality for Filter Stability. CDC (2021)
Tamer Basar, Sean P. Meyn, William R. Perkins
Lecture Notes on Control System Theory and Design. CoRR (2020)
Shuhang Chen, Adithya M. Devraj, Andrey Bernstein, Sean P. Meyn
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation. CoRR (2020)
Yue Chen, Andrey Bernstein, Adithya M. Devraj, Sean P. Meyn
Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow. ACC (2020)
Shuhang Chen, Adithya M. Devraj, Fan Lu, Ana Busic, Sean P. Meyn
Zap Q-Learning With Nonlinear Function Approximation. NeurIPS (2020)
Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation. AISTATS (2020)
Neil Cammardella, Ana Busic, Sean P. Meyn
Simultaneous Allocation and Control of Distributed Energy Resources via Kullback-Leibler-Quadratic Optimal Control. ACC (2020)
Naren Srivaths Raman, Adithya M. Devraj, Prabir Barooah, Sean P. Meyn
Reinforcement Learning for Control of Building HVAC Systems. ACC (2020)
Austin R. Coffman, Neil Cammardella, Prabir Barooah, Sean P. Meyn
Flexibility capacity of thermostatically controlled loads with cycling/lock-out constraints. ACC (2020)
Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn
Diffusion Map-based Algorithm for Gain Function Approximation in the Feedback Particle Filter. SIAM/ASA J. Uncertain. Quantification 8 (3) (2020)
Prashant G. Mehta, Sean P. Meyn
Convex Q-Learning, Part 1: Deterministic Optimal Control. CoRR (2020)
Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn
Zap Q-Learning for Optimal Stopping. ACC (2020)
Adithya M. Devraj, Sean P. Meyn
Q-learning with Uniformly Bounded Variance: Large Discounting is Not a Barrier to Fast Learning. CoRR (2020)
Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation. CoRR (2020)
Neil Cammardella, Ana Busic, Yuting Ji, Sean P. Meyn
Kullback-Leibler-Quadratic Optimal Control of Flexible Power Demand. CDC (2019)
Ana Busic, Sean P. Meyn
Distributed Control of Thermostatically Controlled Loads: Kullback-Leibler Optimal Control in Continuous Time. CDC (2019)
Sepideh Hassan-Moghaddam, Mihailo R. Jovanovic, Sean P. Meyn
Data-driven proximal algorithms for the design of structured optimal feedback gains. ACC (2019)
Austin R. Coffman, Neil Cammardella, Prabir Barooah, Sean P. Meyn
Aggregate capacity of TCLs with cycling constraints. CoRR (2019)
Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn
Gain function approximation in the Feedback Particle Filter. CoRR (2019)
Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn
Zap~Q-Learning for Optimal Stopping Time Problems. CoRR (2019)
Jin-Won Kim, Prashant G. Mehta, Sean P. Meyn
What is the Lagrangian for Nonlinear Filtering? CDC (2019)
Joel Mathias, Robert Moye, Sean P. Meyn, Joseph Warrington
State Space Collapse in Resource Allocation for Demand Dispatch. CDC (2019)
Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn
Zap Q-Learning With Nonlinear Function Approximation. CoRR (2019)
Joel Mathias, Robert Moye, Sean P. Meyn, Joseph Warrington
State Space Collapse in Resource Allocation for Demand Dispatch. CoRR (2019)
Andrey Bernstein, Yue Chen, Marcello Colombino, Emiliano Dall'Anese, Prashant G. Mehta, Sean P. Meyn
Quasi-Stochastic Approximation and Off-Policy Reinforcement Learning. CDC (2019)
Anand Radhakrishnan, Sean P. Meyn
Gain Function Tracking in the Feedback Particle Filter. ACC (2019)
Jin-Won Kim, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn
An Approach to Duality in Nonlinear Filtering. ACC (2019)
Yue Chen, Andrey Bernstein, Adithya M. Devraj, Sean P. Meyn
Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow. CoRR (2019)
Adithya M. Devraj, Ana Busic, Sean P. Meyn
On Matrix Momentum Stochastic Approximation and Applications to Q-learning. Allerton (2019)
Ana Busic, Sean P. Meyn
Ordinary Differential Equation Methods for Markov Decision Processes and Application to Kullback-Leibler Control Cost. SIAM J. Control. Optim. 56 (1) (2018)
Neil Cammardella, Joel Mathias, Matthew Kiener, Ana Busic, Sean P. Meyn
Balancing California's Grid Without Batteries. CDC (2018)
Ana Busic, Sean P. Meyn
Action-Constrained Markov Decision Processes With Kullback-Leibler Cost. COLT (2018)
Anand Radhakrishnan, Sean P. Meyn
Feedback Particle Filter Design Using a Differential-Loss Reproducing Kernel Hilbert Space. ACC (2018)
Yue Chen, Ana Busic, Sean P. Meyn
Estimation and Control of Quality of Service in Demand Dispatch. IEEE Trans. Smart Grid 9 (5) (2018)
Robert Moye, Sean P. Meyn
The Use of Marginal Energy Costs in the Design of U.S. Capacity Markets. HICSS (2018)
Adithya M. Devraj, Ana Busic, Sean P. Meyn
Zap Meets Momentum: Stochastic Approximation Algorithms with Optimal Convergence Rate. CoRR (2018)
Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn
Differential Temporal Difference Learning. CoRR (2018)
Hao Jiang, Uday V. Shanbhag, Sean P. Meyn
Distributed Computation of Equilibria in Misspecified Convex Stochastic Nash Games. IEEE Trans. Autom. Control. 63 (2) (2018)
Joel Mathias, Ana Busic, Sean P. Meyn
Demand Dispatch with Heterogeneous Intelligent Loads. HICSS (2017)
Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn
Error estimates for the kernel gain function approximation in the feedback particle filter. ACC (2017)
Yue Chen, Ana Busic, Sean P. Meyn
State Estimation for the Individual and the Population in Mean Field Control With Application to Demand Dispatch. IEEE Trans. Autom. Control. 62 (3) (2017)
Adithya M. Devraj, Sean P. Meyn
Zap Q-Learning. NIPS (2017)
Adithya M. Devraj, Sean P. Meyn
Fastest Convergence for Q-learning. CoRR (2017)
Ana Busic, Md Umar Hashmi, Sean P. Meyn
Distributed control of a fleet of batteries. ACC (2017)
Tao Yang, Prashant G. Mehta, Sean P. Meyn
Feedback Particle Filter for a Continuous-Time Markov Chain. IEEE Trans. Autom. Control. 61 (2) (2016)
Adithya M. Devraj, Sean P. Meyn
Differential TD learning for value function approximation. CDC (2016)
Ana Busic, Sean P. Meyn
Distributed randomized control for demand dispatch. CDC (2016)
Ehsan Shafieepoorfard, Maxim Raginsky, Sean P. Meyn
Rationally Inattentive Control of Markov Processes. SIAM J. Control. Optim. 54 (2) (2016)
Tao Yang, Richard S. Laugesen, Prashant G. Mehta, Sean P. Meyn
Multivariable feedback particle filter. Autom. 71 (2016)
Yue Chen, Ana Busic, Sean P. Meyn
Ergodic Theory for Controlled Markov Chains with Stationary Inputs. CoRR (2016)
Joel Mathias, Ana Busic, Sean P. Meyn
Demand Dispatch with Heterogeneous Intelligent Loads. CoRR (2016)
Anand Radhakrishnan, Adithya M. Devraj, Sean P. Meyn
Learning techniques for feedback particle filter design. CDC (2016)
Yue Chen, Ana Busic, Sean P. Meyn
Estimation and Control of Quality of Service in Demand Dispatch. CoRR (2016)
Ana Busic, Sean P. Meyn
Distributed Randomized Control for Demand Dispatch. CoRR (2016)
Ana Busic, Sean P. Meyn
Ordinary Differential Equation Methods For Markov Decision Processes and Application to Kullback-Leibler Control Cost. CoRR (2016)
Joel Mathias, Rim Kaddah, Ana Busic, Sean P. Meyn
Smart Fridge / Dumb Grid? Demand Dispatch for the Power Grid of 2020. HICSS (2016)
Adithya M. Devraj, Sean P. Meyn
Differential TD Learning for Value Function Approximation. CoRR (2016)
Sean P. Meyn, Prabir Barooah, Ana Busic, Yue Chen, Jordan Ehren
Ancillary Service to the Grid Using Intelligent Deferrable Loads. IEEE Trans. Autom. Control. 60 (11) (2015)
Ehsan Shafieepoorfard, Maxim Raginsky, Sean P. Meyn
Rationally inattentive control of Markov processes. CoRR (2015)
Prabir Barooah, Ana Busic, Sean P. Meyn
Spectral Decomposition of Demand-Side Flexibility for Reliable Ancillary Services in a Smart Grid. HICSS (2015)
Yue Chen, Ana Busic, Sean P. Meyn
State Estimation and Mean Field Control with Application to Demand Dispatch. CoRR (2015)
Ana Busic, Sean P. Meyn
Approximate optimality with bounded regret in dynamic matching models. SIGMETRICS Perform. Evaluation Rev. 43 (2) (2015)
Yashen Lin, Prabir Barooah, Sean P. Meyn, Timothy Middelkoop
Experimental Evaluation of Frequency Regulation From Commercial Building HVAC Systems. IEEE Trans. Smart Grid 6 (2) (2015)
Richard S. Laugesen, Prashant G. Mehta, Sean P. Meyn, Maxim Raginsky
Poisson's Equation in Nonlinear Filtering. SIAM J. Control. Optim. 53 (1) (2015)
Joel Mathias, Rim Kaddah, Ana Busic, Sean P. Meyn
Smart Fridge / Dumb Grid? Demand Dispatch for the Power Grid of 2020. CoRR (2015)
Yue Chen, Ana Busic, Sean P. Meyn
State estimation and mean field control with application to demand dispatch. CDC (2015)
Yashen Lin, Prabir Barooah, Sean P. Meyn, Timothy Middelkoop
Demand side frequency regulation from commercial building HVAC systems: An experimental study. ACC (2015)
Sean P. Meyn, Prabir Barooah, Ana Busic, Yue Chen, Jordan Ehren
Ancillary Service to the Grid Using Intelligent Deferrable Loads. CoRR (2014)
Richard S. Laugesen, Prashant G. Mehta, Sean P. Meyn, Maxim Raginsky
Poisson's equation in nonlinear filtering. CDC (2014)
Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday V. Shanbhag
On the Efficiency of Equilibria in Mean-Field Oscillator Games. Dyn. Games Appl. 4 (2) (2014)
He Hao, Yashen Lin, Anupama Kowli, Prabir Barooah, Sean P. Meyn
Ancillary Service to the Grid Through Control of Fans in Commercial Building HVAC Systems. IEEE Trans. Smart Grid 5 (4) (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sean P. Meyn