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ORCIDSean P. Meyn
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- affiliation: University of Florida, Gainesville, USA
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2020 – today
- 2024
[c118]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: 1-5- [c117]Gian Paramo, Arturo S. Bretas, Sean P. Meyn:
Microgrid Frequency Stability: A Proactive Scheme Based on Dynamic Predictions. ISGT 2024: 1-5 - [i48]Austin Cooper, Sean P. Meyn:
Reinforcement Learning Design for Quickest Change Detection. CoRR abs/2403.14109 (2024) - [i47]Anant A. Joshi, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn:
Dual Ensemble Kalman Filter for Stochastic Optimal Control. CoRR abs/2404.06696 (2024) - [i46]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 abs/2406.11057 (2024) - [i45]Austin Cooper, Sean P. Meyn:
Quickest Change Detection Using Mismatched CUSUM. CoRR abs/2409.07948 (2024) - 2023
- [j65]Neil Cammardella, Ana Busic, Sean P. Meyn:
Kullback-Leibler-Quadratic Optimal Control. SIAM J. Control. Optim. 61(5): 3234-3258 (2023) - [j64]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): 7616-7628 (2023) - [j63]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): 1830-1843 (2023) - [c116]Caio Kalil Lauand, Ana Busic, Sean P. Meyn:
Inverse Free Zap Stochastic Approximation Extended Abstract. Allerton 2023: 1-4 - [c115]Ana Busic, Sean P. Meyn, Neil Cammardella:
Learning Optimal Policies in Mean Field Models with Kullback-Leibler Regularization. CDC 2023: 38-45 - [c114]Fan Lu, Sean P. Meyn:
Convex Q Learning in a Stochastic Environment. CDC 2023: 776-781 - [c113]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: 1529-1536 - [c112]Sean P. Meyn, Fan Lu, Joel Mathias:
Balancing the Power Grid with Cheap Assets. CDC 2023: 4012-4017 - [c111]Caio Kalil Lauand, Sean P. Meyn:
The Curse of Memory in Stochastic Approximation. CDC 2023: 7803-7809 - [c110]Austin Cooper, Arturo S. Bretas, Sean P. Meyn, Newton G. Bretas:
High Impedance Fault Detection Through Quasi-Static State Estimation: A Parameter Error Modeling Approach. ISGT 2023: 1-5 - [c109]Gian Paramo, Arturo S. Bretas, Sean P. Meyn:
High-Impedance Non-Linear Fault Detection via Eigenvalue Analysis with low PMU Sampling Rates. ISGT 2023: 1-5 - [i44]Gian Paramo, Arturo S. Bretas, Sean P. Meyn:
High-Impedance Non-Linear Fault Detection via Eigenvalue Analysis with low PMU Sampling Rates. CoRR abs/2301.04123 (2023) - [i43]Sean P. Meyn:
Stability of Q-Learning Through Design and Optimism. CoRR abs/2307.02632 (2023) - [i42]Fan Lu, Sean P. Meyn:
Convex Q Learning in a Stochastic Environment: Extended Version. CoRR abs/2309.05105 (2023) - 2022
- [j62]Anant A. Joshi, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn:
Controlled interacting particle algorithms for simulation-based reinforcement learning. Syst. Control. Lett. 170: 105392 (2022) - [j61]Adithya M. Devraj, Sean P. Meyn:
Q-Learning With Uniformly Bounded Variance. IEEE Trans. Autom. Control. 67(11): 5948-5963 (2022) - [c108]Caio Kalil Lauand, Sean P. Meyn:
Bias in Stochastic Approximation Cannot Be Eliminated With Averaging. Allerton 2022: 1-4 - [c107]Fan Lu, Prashant G. Mehta, Sean P. Meyn, Gergely Neu:
Convex Analytic Theory for Convex Q-Learning. CDC 2022: 4065-4071 - [c106]Joel Mathias, Sean P. Meyn, Hala Ballouz, Meisam Ansari:
A Distributed Control Architecture for Optimal Allocation of Grid-responsive Load Aggregations. ISGT 2022: 1-5 - [c105]Caio Kalil Lauand, Sean P. Meyn:
Approaching Quartic Convergence Rates for Quasi-Stochastic Approximation with Application to Gradient-Free Optimization. NeurIPS 2022 - [i41]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 abs/2210.08131 (2022) - [i40]Fan Lu, Prashant G. Mehta, Sean P. Meyn, Gergely Neu:
Sufficient Exploration for Convex Q-learning. CoRR abs/2210.09409 (2022) - [i39]Austin Cooper, Arturo S. Bretas, Sean P. Meyn, Newton G. Bretas:
Uncertainty Error Modeling for Non-Linear State Estimation With Unsynchronized SCADA and μPMU Measurements. CoRR abs/2212.09987 (2022) - [i38]Austin Cooper, Arturo S. Bretas, Sean P. Meyn, Newton G. Bretas:
High Impedance Fault Detection Through Quasi-Static State Estimation: A Parameter Error Modeling Approach. CoRR abs/2212.09989 (2022) - 2021
- [j60]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): 1681-1702 (2021) - [j59]Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn:
Differential Temporal Difference Learning. IEEE Trans. Autom. Control. 66(10): 4652-4667 (2021) - [c104]Naren Srivaths Raman, Ninad Gaikwad, Prabir Barooah, Sean P. Meyn:
Reinforcement Learning-Based Home Energy Management System for Resiliency. ACC 2021: 1358-1364 - [c103]Shuhang Chen, Adithya M. Devraj, Andrey Bernstein, Sean P. Meyn:
Accelerating Optimization and Reinforcement Learning with Quasi Stochastic Approximation. ACC 2021: 1965-1972 - [c102]Fan Lu, Prashant G. Mehta, Sean P. Meyn, Gergely Neu:
Convex Q-Learning. ACC 2021: 4749-4756 - [c101]Neil Cammardella, Ana Busic, Sean P. Meyn:
Kullback-Leibler-Quadratic Optimal Control in a Stochastic Environment. CDC 2021: 158-165 - [c100]Jin-Won Kim, Prashant G. Mehta, Sean P. Meyn:
The Conditional Poincaré Inequality for Filter Stability. CDC 2021: 1629-1636 - [i37]Hala Ballouz, Joel Mathias, Sean P. Meyn, Robert Moye, Joseph Warrington:
Reliable Power Grid: Long Overdue Alternatives to Surge Pricing. CoRR abs/2103.06355 (2021) - [i36]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 abs/2110.14427 (2021) - 2020
- [j58]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): 1090-1117 (2020) - [c99]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation. AISTATS 2020: 4173-4183 - [c98]Neil Cammardella, Ana Busic, Sean P. Meyn:
Simultaneous Allocation and Control of Distributed Energy Resources via Kullback-Leibler-Quadratic Optimal Control. ACC 2020: 514-520 - [c97]Austin R. Coffman, Neil Cammardella, Prabir Barooah, Sean P. Meyn:
Flexibility capacity of thermostatically controlled loads with cycling/lock-out constraints. ACC 2020: 527-532 - [c96]Naren Srivaths Raman, Adithya M. Devraj, Prabir Barooah, Sean P. Meyn:
Reinforcement Learning for Control of Building HVAC Systems. ACC 2020: 2326-2332 - [c95]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: 3140-3147 - [c94]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Zap Q-Learning for Optimal Stopping. ACC 2020: 3920-3925 - [c93]Shuhang Chen, Adithya M. Devraj, Fan Lu, Ana Busic, Sean P. Meyn:
Zap Q-Learning With Nonlinear Function Approximation. NeurIPS 2020 - [i35]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation. CoRR abs/2002.02584 (2020) - [i34]Adithya M. Devraj, Sean P. Meyn:
Q-learning with Uniformly Bounded Variance: Large Discounting is Not a Barrier to Fast Learning. CoRR abs/2002.10301 (2020) - [i33]Tamer Basar, Sean P. Meyn, William R. Perkins:
Lecture Notes on Control System Theory and Design. CoRR abs/2007.01367 (2020) - [i32]Prashant G. Mehta, Sean P. Meyn:
Convex Q-Learning, Part 1: Deterministic Optimal Control. CoRR abs/2008.03559 (2020) - [i31]Shuhang Chen, Adithya M. Devraj, Andrey Bernstein, Sean P. Meyn:
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation. CoRR abs/2009.14431 (2020)
2010 – 2019
- 2019
- [c92]Adithya M. Devraj, Ana Busic, Sean P. Meyn:
On Matrix Momentum Stochastic Approximation and Applications to Q-learning. Allerton 2019: 749-756 - [c91]Anand Radhakrishnan, Sean P. Meyn:
Gain Function Tracking in the Feedback Particle Filter. ACC 2019: 5352-5359 - [c90]Jin-Won Kim, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn:
An Approach to Duality in Nonlinear Filtering. ACC 2019: 5360-5365 - [c89]Sepideh Hassan-Moghaddam, Mihailo R. Jovanovic, Sean P. Meyn:
Data-driven proximal algorithms for the design of structured optimal feedback gains. ACC 2019: 5846-5850 - [c88]Jin-Won Kim, Prashant G. Mehta, Sean P. Meyn:
What is the Lagrangian for Nonlinear Filtering? CDC 2019: 1607-1614 - [c87]Neil Cammardella, Ana Busic, Yuting Ji, Sean P. Meyn:
Kullback-Leibler-Quadratic Optimal Control of Flexible Power Demand. CDC 2019: 4195-4201 - [c86]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: 5244-5251 - [c85]Joel Mathias, Robert Moye, Sean P. Meyn, Joseph Warrington:
State Space Collapse in Resource Allocation for Demand Dispatch. CDC 2019: 6181-6188 - [c84]Ana Busic, Sean P. Meyn:
Distributed Control of Thermostatically Controlled Loads: Kullback-Leibler Optimal Control in Continuous Time. CDC 2019: 7258-7265 - [i30]Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn:
Gain function approximation in the Feedback Particle Filter. CoRR abs/1902.07263 (2019) - [i29]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Zap~Q-Learning for Optimal Stopping Time Problems. CoRR abs/1904.11538 (2019) - [i28]Joel Mathias, Robert Moye, Sean P. Meyn, Joseph Warrington:
State Space Collapse in Resource Allocation for Demand Dispatch. CoRR abs/1909.06869 (2019) - [i27]Austin R. Coffman, Neil Cammardella, Prabir Barooah, Sean P. Meyn:
Aggregate capacity of TCLs with cycling constraints. CoRR abs/1909.11497 (2019) - [i26]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 abs/1909.13132 (2019) - [i25]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Zap Q-Learning With Nonlinear Function Approximation. CoRR abs/1910.05405 (2019) - 2018
- [j57]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): 343-366 (2018) - [j56]Hao Jiang, Uday V. Shanbhag, Sean P. Meyn:
Distributed Computation of Equilibria in Misspecified Convex Stochastic Nash Games. IEEE Trans. Autom. Control. 63(2): 360-371 (2018) - [j55]Yue Chen, Ana Busic, Sean P. Meyn:
Estimation and Control of Quality of Service in Demand Dispatch. IEEE Trans. Smart Grid 9(5): 5348-5356 (2018) - [c83]Anand Radhakrishnan, Sean P. Meyn:
Feedback Particle Filter Design Using a Differential-Loss Reproducing Kernel Hilbert Space. ACC 2018: 329-336 - [c82]Neil Cammardella, Joel Mathias, Matthew Kiener, Ana Busic, Sean P. Meyn:
Balancing California's Grid Without Batteries. CDC 2018: 7314-7321 - [c81]Ana Busic, Sean P. Meyn:
Action-Constrained Markov Decision Processes With Kullback-Leibler Cost. COLT 2018: 1431-1444 - [c80]Robert Moye, Sean P. Meyn:
The Use of Marginal Energy Costs in the Design of U.S. Capacity Markets. HICSS 2018: 1-10 - [i24]Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Zap Meets Momentum: Stochastic Approximation Algorithms with Optimal Convergence Rate. CoRR abs/1809.06277 (2018) - [i23]Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn:
Differential Temporal Difference Learning. CoRR abs/1812.11137 (2018) - 2017
- [j54]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): 1138-1149 (2017) - [c79]Ana Busic, Md Umar Hashmi, Sean P. Meyn:
Distributed control of a fleet of batteries. ACC 2017: 3406-3411 - [c78]Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn:
Error estimates for the kernel gain function approximation in the feedback particle filter. ACC 2017: 4576-4582 - [c77]Joel Mathias, Ana Busic, Sean P. Meyn:
Demand Dispatch with Heterogeneous Intelligent Loads. HICSS 2017: 1-10 - [c76]Adithya M. Devraj, Sean P. Meyn:
Zap Q-Learning. NIPS 2017: 2235-2244 - [i22]Adithya M. Devraj, Sean P. Meyn:
Fastest Convergence for Q-learning. CoRR abs/1707.03770 (2017) - 2016
- [j53]Tao Yang, Richard S. Laugesen, Prashant G. Mehta, Sean P. Meyn:
Multivariable feedback particle filter. Autom. 71: 10-23 (2016) - [j52]Ehsan Shafieepoorfard, Maxim Raginsky, Sean P. Meyn:
Rationally Inattentive Control of Markov Processes. SIAM J. Control. Optim. 54(2): 987-1016 (2016) - [j51]Tao Yang, Prashant G. Mehta, Sean P. Meyn:
Feedback Particle Filter for a Continuous-Time Markov Chain. IEEE Trans. Autom. Control. 61(2): 556-561 (2016) - [c75]Anand Radhakrishnan, Adithya M. Devraj, Sean P. Meyn:
Learning techniques for feedback particle filter design. CDC 2016: 5453-5459 - [c74]Adithya M. Devraj, Sean P. Meyn:
Differential TD learning for value function approximation. CDC 2016: 6347-6354 - [c73]Ana Busic, Sean P. Meyn:
Distributed randomized control for demand dispatch. CDC 2016: 6964-6971 - [c72]Joel Mathias, Rim Kaddah, Ana Busic, Sean P. Meyn:
Smart Fridge / Dumb Grid? Demand Dispatch for the Power Grid of 2020. HICSS 2016: 2498-2507 - [i21]Ana Busic, Sean P. Meyn:
Distributed Randomized Control for Demand Dispatch. CoRR abs/1603.05966 (2016) - [i20]Adithya M. Devraj, Sean P. Meyn:
Differential TD Learning for Value Function Approximation. CoRR abs/1604.01828 (2016) - [i19]Yue Chen, Ana Busic, Sean P. Meyn:
Ergodic Theory for Controlled Markov Chains with Stationary Inputs. CoRR abs/1604.04013 (2016) - [i18]Ana Busic, Sean P. Meyn:
Ordinary Differential Equation Methods For Markov Decision Processes and Application to Kullback-Leibler Control Cost. CoRR abs/1605.04591 (2016) - [i17]Yue Chen, Ana Busic, Sean P. Meyn:
Estimation and Control of Quality of Service in Demand Dispatch. CoRR abs/1609.00051 (2016) - [i16]Joel Mathias, Ana Busic, Sean P. Meyn:
Demand Dispatch with Heterogeneous Intelligent Loads. CoRR abs/1610.00813 (2016) - 2015
- [j50]Richard S. Laugesen, Prashant G. Mehta, Sean P. Meyn, Maxim Raginsky:
Poisson's Equation in Nonlinear Filtering. SIAM J. Control. Optim. 53(1): 501-525 (2015) - [j49]Ana Busic, Sean P. Meyn:
Approximate optimality with bounded regret in dynamic matching models. SIGMETRICS Perform. Evaluation Rev. 43(2): 75-77 (2015) - [j48]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): 2847-2862 (2015) - [j47]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): 776-783 (2015) - [c71]Yashen Lin, Prabir Barooah, Sean P. Meyn, Timothy Middelkoop:
Demand side frequency regulation from commercial building HVAC systems: An experimental study. ACC 2015: 3019-3024 - [c70]Yue Chen, Ana Busic, Sean P. Meyn:
State estimation and mean field control with application to demand dispatch. CDC 2015: 6548-6555 - [c69]Prabir Barooah, Ana Busic, Sean P. Meyn:
Spectral Decomposition of Demand-Side Flexibility for Reliable Ancillary Services in a Smart Grid. HICSS 2015: 2700-2709 - [i15]Ehsan Shafieepoorfard, Maxim Raginsky, Sean P. Meyn:
Rationally inattentive control of Markov processes. CoRR abs/1502.03762 (2015) - [i14]Yue Chen, Ana Busic, Sean P. Meyn:
State Estimation and Mean Field Control with Application to Demand Dispatch. CoRR abs/1504.00088 (2015) - [i13]Joel Mathias, Rim Kaddah, Ana Busic, Sean P. Meyn:
Smart Fridge / Dumb Grid? Demand Dispatch for the Power Grid of 2020. CoRR abs/1509.01531 (2015) - 2014
- [j46]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): 177-207 (2014) - [j45]Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday V. Shanbhag:
Learning in Mean-Field Games. IEEE Trans. Autom. Control. 59(3): 629-644 (2014) - [j44]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): 2066-2074 (2014) - [c68]Ana Busic, Sean P. Meyn:
Passive dynamics in mean field control. CDC 2014: 2716-2721 - [c67]Richard S. Laugesen, Prashant G. Mehta, Sean P. Meyn, Maxim Raginsky:
Poisson's equation in nonlinear filtering. CDC 2014: 4185-4190 - [c66]Yue Chen, Ana Busic, Sean P. Meyn:
Individual risk in mean field control with application to automated demand response. CDC 2014: 6425-6432 - [i12]Sean P. Meyn, Prabir Barooah, Ana Busic, Yue Chen, Jordan Ehren:
Ancillary Service to the Grid Using Intelligent Deferrable Loads. CoRR abs/1402.4600 (2014) - [i11]Ana Busic, Sean P. Meyn:
Passive Dynamics in Mean Field Control. CoRR abs/1402.4618 (2014) - [i10]Yue Chen, Ana Busic, Sean P. Meyn:
Individual risk in mean-field control models for decentralized control, with application to automated demand response. CoRR abs/1409.6941 (2014) - [i9]Ana Busic, Sean P. Meyn:
Optimization of Dynamic Matching Models. CoRR abs/1411.1044 (2014) - 2013
- [j43]Qing Zhao, Edwin K. P. Chong, Bhaskar Krishnamachari, Amir Leshem, Sean P. Meyn, Venugopal V. Veeravalli:
Introduction to the Issue on Learning-Based Decision Making in Dynamic Systems Under Uncertainty. IEEE J. Sel. Top. Signal Process. 7(5): 743-745 (2013) - [j42]Jose H. Blanchet, Peter W. Glynn, Sean P. Meyn:
Large deviations for the empirical mean of an M/M/1 queue. Queueing Syst. Theory Appl. 73(4): 425-446 (2013) - [j41]Serdar Yüksel, Sean P. Meyn:
Random-Time, State-Dependent Stochastic Drift for Markov Chains and Application to Stochastic Stabilization Over Erasure Channels. IEEE Trans. Autom. Control. 58(1): 47-59 (2013) - [j40]Tao Yang, Prashant G. Mehta, Sean P. Meyn:
Feedback Particle Filter. IEEE Trans. Autom. Control. 58(10): 2465-2480 (2013) - [j39]Dayu Huang, Sean P. Meyn:
Generalized Error Exponents for Small Sample Universal Hypothesis Testing. IEEE Trans. Inf. Theory 59(12): 8157-8181 (2013) - [c65]He Hao, Anupama Kowli, Yashen Lin, Prabir Barooah, Sean P. Meyn:
Ancillary service for the grid via control of commercial building HVAC systems. ACC 2013: 467-472 - [c64]Adam K. Tilton, Prashant G. Mehta, Sean P. Meyn:
Multi-dimensional feedback particle filter for coupled oscillators. ACC 2013: 2415-2421 - [c63]Tao Yang, Prashant G. Mehta, Sean P. Meyn:
Feedback particle filter for a continuous-time Markov chain. ACC 2013: 6772-6777 - [c62]Ehsan Shafieepoorfard, Maxim Raginsky, Sean P. Meyn:
Rational inattention in controlled Markov processes. ACC 2013: 6790-6797 - [c61]Prashant G. Mehta, Sean P. Meyn:
A feedback particle filter-based approach to optimal control with partial observations. CDC 2013: 3121-3127 - [c60]Sean P. Meyn, Prabir Barooah, Ana Busic, Jordan Ehren:
Ancillary service to the grid from deferrable loads: The case for intelligent pool pumps in Florida. CDC 2013: 6946-6953 - [c59]Yashen Lin, Prabir Barooah, Sean P. Meyn:
Low-frequency power-grid ancillary services from commercial building HVAC systems. SmartGridComm 2013: 169-174 - [i8]Wei Chen, Dayu Huang, Ankur A. Kulkarni, Jayakrishnan Unnikrishnan, Quanyan Zhu, Prashant G. Mehta, Sean P. Meyn, Adam Wierman:
Approximate dynamic programming using fluid and diffusion approximations with applications to power management. CoRR abs/1307.1759 (2013) - 2012
- [j38]Vivek S. Borkar, Sean P. Meyn:
Oja's algorithm for graph clustering, Markov spectral decomposition, and risk sensitive control. Autom. 48(10): 2512-2519 (2012) - [j37]Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday V. Shanbhag:
Synchronization of Coupled Oscillators is a Game. IEEE Trans. Autom. Control. 57(4): 920-935 (2012) - [c58]He Hao, Timothy Middelkoop, Prabir Barooah, Sean P. Meyn:
How demand response from commercial buildings will provide the regulation needs of the grid. Allerton Conference 2012: 1908-1913 - [c57]Gui Wang, Uday V. Shanbhag, Sean P. Meyn:
On Nash equilibria in duopolistic power markets subject to make-whole uplift. CDC 2012: 472-477 - [c56]Tao Yang, Richard S. Laugesen, Prashant G. Mehta, Sean P. Meyn:
Multivariable feedback particle filter. CDC 2012: 4063-4070 - [c55]Dayu Huang, Sean P. Meyn:
Feature selection for composite hypothesis testing with small samples: Fundamental limits and algorithms. ICASSP 2012: 1917-1920 - [c54]Dayu Huang, Sean P. Meyn:
Error exponents for composite hypothesis testing with small samples. ICASSP 2012: 3261-3264 - [c53]Gui Wang, Matias Negrete-Pincetic, Anupama Kowli, Ehsan Shafieepoorfard, Sean P. Meyn, Uday V. Shanbhag:
Real-time prices in an entropic grid. ISGT 2012: 1-8 - [c52]Dayu Huang, Sean P. Meyn:
Classification with high-dimensional sparse samples. ISIT 2012: 2586-2590 - [c51]Dayu Huang, Sean P. Meyn:
Optimality of coincidence-based goodness of fit test for sparse sample problems. ITA 2012: 344-346 - [i7]Dayu Huang, Sean P. Meyn:
Classification with High-Dimensional Sparse Samples. CoRR abs/1202.1574 (2012) - [i6]Dayu Huang, Sean P. Meyn:
Generalized Error Exponents for Sparse Sample Goodness of Fit Tests. CoRR abs/1204.1563 (2012) - 2011
- [j36]Ken R. Duffy, Sean P. Meyn:
Estimating Loynes' exponent. Queueing Syst. Theory Appl. 68(3-4): 285-293 (2011) - [j35]Kun Deng, Prashant G. Mehta, Sean P. Meyn:
Optimal Kullback-Leibler Aggregation via Spectral Theory of Markov Chains. IEEE Trans. Autom. Control. 56(12): 2793-2808 (2011) - [j34]Jayakrishnan Unnikrishnan, Dayu Huang, Sean P. Meyn, Amit Surana, Venugopal V. Veeravalli:
Universal and Composite Hypothesis Testing via Mismatched Divergence. IEEE Trans. Inf. Theory 57(3): 1587-1603 (2011) - [j33]Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli, Sean P. Meyn:
Minimax Robust Quickest Change Detection. IEEE Trans. Inf. Theory 57(3): 1604-1614 (2011) - [c50]Tao Yang, Prashant G. Mehta, Sean P. Meyn:
A mean-field control-oriented approach to particle filtering. ACC 2011: 2037-2043 - [c49]Darshan Shirodkar, Sean P. Meyn:
Quasi stochastic approximation. ACC 2011: 2429-2435 - [c48]Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday V. Shanbhag:
On the efficiency of equilibria in mean-field oscillator games. ACC 2011: 5354-5359 - [c47]Sean P. Meyn, Amit Surana:
TD-learning with exploration. CDC/ECC 2011: 148-155 - [c46]Hao Jiang, Uday V. Shanbhag, Sean P. Meyn:
Learning equilibria in constrained Nash-Cournot games with misspecified demand functions. CDC/ECC 2011: 1018-1023 - [c45]Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday V. Shanbhag:
Bifurcation analysis of a heterogeneous mean-field oscillator game model. CDC/ECC 2011: 3895-3900 - [c44]Kun Deng, Prashant G. Mehta, Sean P. Meyn, Mathukumalli Vidyasagar:
A recursive learning algorithm for model reduction of Hidden Markov Models. CDC/ECC 2011: 4674-4679 - [c43]Tao Yang, Prashant G. Mehta, Sean P. Meyn:
Feedback particle filter with mean-field coupling. CDC/ECC 2011: 7909-7916 - 2010
- [j32]Ken R. Duffy, Sean P. Meyn:
Most likely paths to error when estimating the mean of a reflected random walk. Perform. Evaluation 67(12): 1290-1303 (2010) - [j31]David Gamarnik, Sean P. Meyn:
On exponential ergodicity of multiclass queueing networks. Queueing Syst. Theory Appl. 65(2): 109-133 (2010) - [j30]Olgica Milenkovic, Gil Alterovitz, Gerard Battail, Todd P. Coleman, Joachim Hagenauer, Sean P. Meyn, Nathan D. Price, Marco Ramoni, Ilya Shmulevich, Wojciech Szpankowski:
Introduction to the special issue on information theory in molecular biology and neuroscience. IEEE Trans. Inf. Theory 56(2): 649-652 (2010) - [j29]Che Lin, Venugopal V. Veeravalli, Sean P. Meyn:
A Random Search Framework for Convergence Analysis of Distributed Beamforming With Feedback. IEEE Trans. Inf. Theory 56(12): 6133-6141 (2010) - [c42]P. Viswanath, Sean P. Meyn:
Foreword. Allerton 2010: 1 - [c41]Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday V. Shanbhag:
Synchronization of coupled oscillators is a game. ACC 2010: 1783-1790 - [c40]Kun Deng, Prabir Barooah, Prashant G. Mehta, Sean P. Meyn:
Building thermal model reduction via aggregation of states. ACC 2010: 5118-5123 - [c39]Sean P. Meyn, Matias Negrete-Pincetic, Gui Wang, Anupama Kowli, Ehsan Shafieepoorfard:
The value of volatile resources in electricity markets. CDC 2010: 1029-1036 - [c38]Sean P. Meyn, Wei Chen, Daniel O'Neill:
Optimal cross-layer wireless control policies using TD learning. CDC 2010: 1951-1956 - [c37]Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday V. Shanbhag:
Learning in mean-field oscillator games. CDC 2010: 3125-3132 - [c36]Kun Deng, Prashant G. Mehta, Sean P. Meyn:
Aggregation-based model reduction of a Hidden Markov Model. CDC 2010: 6183-6188 - [c35]Dayu Huang, Sean P. Meyn:
Feature extraction for universal hypothesis testing via rank-constrained optimization. ISIT 2010: 1618-1622 - [c34]Jayakrishnan Unnikrishnan, Sean P. Meyn, Venugopal V. Veeravalli:
On thresholds for robust goodness-of-fit tests. ITW 2010: 1-4 - [c33]Shankar Sadasivam, Pierre Moulin, Sean P. Meyn:
A universal divergence-rate estimator for steganalysis in timing channels. WIFS 2010: 1-6 - [i5]Dayu Huang, Sean P. Meyn:
Feature Extraction for Universal Hypothesis Testing via Rank-constrained Optimization. CoRR abs/1001.3090 (2010) - [i4]Serdar Yüksel, Sean P. Meyn:
Random-Time, State-Dependent Stochastic Drift for Markov Chains and Application to Stochastic Stabilization Over Erasure Channels. CoRR abs/1010.4820 (2010)
2000 – 2009
- 2009
- [j28]Wei Chen, Danail Traskov, Michael Heindlmaier, Muriel Médard, Sean P. Meyn, Asuman E. Ozdaglar:
Coding and control for communication networks. Queueing Syst. Theory Appl. 63(1-4): 195-216 (2009) - [j27]Sean P. Meyn:
Stability and Asymptotic Optimality of Generalized MaxWeight Policies. SIAM J. Control. Optim. 47(6): 3259-3294 (2009) - [c32]Kun Deng, Yu Sun, Prashant G. Mehta, Sean P. Meyn:
An information-theoretic framework to aggregate a Markov chain. ACC 2009: 731-736 - [c31]Sean P. Meyn, Amit Surana, Yiqing Lin, Stella Maris Oggianu, Satish Narayanan, Thomas A. Frewen:
A sensor-utility-network method for estimation of occupancy in buildings. CDC 2009: 1494-1500 - [c30]Wei Chen, Dayu Huang, Ankur A. Kulkarni, Jayakrishnan Unnikrishnan, Quanyan Zhu, Prashant G. Mehta, Sean P. Meyn, Adam Wierman:
Approximate dynamic programming using fluid and diffusion approximations with applications to power management. CDC 2009: 3575-3580 - [c29]Prashant G. Mehta, Sean P. Meyn:
Q-learning and Pontryagin's Minimum Principle. CDC 2009: 3598-3605 - [c28]Sean P. Meyn, Amit Surana, Yiqing Lin, Satish Narayanan:
Anomaly detection using projective Markov models in a distributed sensor network. CDC 2009: 4662-4669 - [c27]Kun Deng, Prashant G. Mehta, Sean P. Meyn:
A simulation-based method for aggregating Markov chains. CDC 2009: 4710-4716 - [c26]Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli, Sean P. Meyn:
Least favorable distributions for robust quickest change detection. ISIT 2009: 649-653 - [c25]Dayu Huang, Jayakrishnan Unnikrishnan, Sean P. Meyn, Venugopal V. Veeravalli, Amit Surana:
Statistical SVMs for robust detection, supervised learning, and universal classification. ITW 2009: 62-66 - [i3]Jayakrishnan Unnikrishnan, Dayu Huang, Sean P. Meyn, Amit Surana, Venugopal V. Veeravalli:
Universal and Composite Hypothesis Testing via Mismatched Divergence. CoRR abs/0909.2234 (2009) - [i2]Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli, Sean P. Meyn:
Minimax Robust Quickest Change Detection. CoRR abs/0911.2551 (2009) - 2008
- [c24]Joshua D. Isom, Sean P. Meyn, Richard D. Braatz:
Piecewise Linear Dynamic Programming for Constrained POMDPs. AAAI 2008: 291-296 - [c23]Joseph S. Niedbalski, Kun Deng, Prashant G. Mehta, Sean P. Meyn:
Model reduction for reduced order estimation in traffic models. ACC 2008: 914-919 - [c22]Yu Sun, Prashant G. Mehta, Sean P. Meyn:
Belief propagation in feedback systems: Connections to bode and observability. ACC 2008: 1268-1273 - [c21]Sean P. Meyn, Gregory Hagen, George Mathew, Andrzej Banaszuk:
On complex spectra and metastability of Markov models. CDC 2008: 3835-3839 - [c20]Sean P. Meyn, George Mathew:
Shannon meets Bellman: Feature based Markovian models for detection and optimization. CDC 2008: 5558-5564 - [c19]Kun Deng, Wei Chen, Prashant G. Mehta, Sean P. Meyn:
Resource pooling for optimal evacuation of a large building. CDC 2008: 5565-5570 - [c18]Francisco S. Melo, Sean P. Meyn, M. Isabel Ribeiro:
An analysis of reinforcement learning with function approximation. ICML 2008: 664-671 - [c17]Sofia Kyriazopoulou-Panagiotopoulou, Ioannis Kontoyiannis, Sean P. Meyn:
Control variates as screening functions. VALUETOOLS 2008: 28 - [c16]Vivek S. Borkar, Sean P. Meyn:
Oja's algorithm for graph clustering and Markov spectral decomposition. VALUETOOLS 2008: 29 - [i1]Che Lin, Venugopal V. Veeravalli, Sean P. Meyn:
Distributed Beamforming with Feedback: Convergence Analysis. CoRR abs/0806.3023 (2008) - 2007
- [c15]Sean P. Meyn:
Myopic policies and maxweight policies for stochastic networks. CDC 2007: 639-646 - [c14]In-Koo Cho, Sean P. Meyn:
Efficiency and marginal cost pricing in dynamic competitive markets with friction. CDC 2007: 771-778 - 2006
- [j26]Mike Chen, In-Koo Cho, Sean P. Meyn:
Reliability by design in distributed power transmission networks. Autom. 42(8): 1267-1281 (2006) - [j25]Jianyi Huang, Sean P. Meyn, Muriel Médard:
Error Exponents for Channel Coding With Application to Signal Constellation Design. IEEE J. Sel. Areas Commun. 24(8): 1647-1661 (2006) - [j24]Charuhas Pandit, Sean P. Meyn:
Robust Measurement-Based Admission Control Using Markov's Theory of Canonical Distributions. IEEE Trans. Inf. Theory 52(10): 4504-4518 (2006) - [c13]Gersende Fort, Eric Moulines, Sean P. Meyn, Pierre Priouret:
ODE methods for Markov chain stability with applications to MCMC. VALUETOOLS 2006: 42 - [c12]Ioannis Kontoyiannis, Luis Alfonso Lastras-Montaño, Sean P. Meyn:
Exponential bounds and stopping rules for MCMC and general Markov chains. VALUETOOLS 2006: 45 - 2005
- [j23]Sean P. Meyn:
Dynamic Safety-Stocks for Asymptotic Optimality in Stochastic Networks. Queueing Syst. Theory Appl. 50(2-3): 255-297 (2005) - [j22]Sean P. Meyn:
Workload Models for Stochastic Networks: Value Functions and Performance Evaluation. IEEE Trans. Autom. Control. 50(8): 1106-1122 (2005) - [j21]Jianyi Huang, Sean P. Meyn:
Characterization and computation of optimal distributions for channel coding. IEEE Trans. Inf. Theory 51(7): 2336-2351 (2005) - [c11]Ioannis Kontoyiannis, Luis Alfonso Lastras-Montaño, Sean P. Meyn:
Relative entropy and exponential deviation bounds for general Markov chains. ISIT 2005: 1563-1567 - 2004
- [j20]Mike Chen, Richard Dubrawski, Sean P. Meyn:
Management of demand-driven production systems. IEEE Trans. Autom. Control. 49(5): 686-698 (2004) - [j19]Muriel Médard, Jianyi Huang, Andrea J. Goldsmith, Sean P. Meyn, Todd P. Coleman:
Capacity of time-slotted ALOHA packetized multiple-access systems over the AWGN channel. IEEE Trans. Wirel. Commun. 3(2): 486-499 (2004) - [c10]Sean P. Meyn:
Dynamic safety-stocks for asymptotic optimality in stochastic networks. CDC 2004: 3930-3937 - [c9]Charuhas Pandit, Sean P. Meyn, Venugopal V. Veeravalli:
Asymptotic robust Neyman-Pearson hypothesis testing based on moment classes. ISIT 2004: 220 - [c8]Jianyi Huang, Sean P. Meyn, Muriel Médard:
Error exponents for channel coding and signal constellation design. ISIT 2004: 478 - [c7]Charuhas Pandit, Jianyi Huang, Sean P. Meyn, Venugopal V. Veeravalli:
Extremal distributions in information theory and hypothesis testing. ITW 2004: 76-81 - 2003
- [j18]Shane G. Henderson, Sean P. Meyn, Vladislav B. Tadic:
Performance Evaluation and Policy Selection in Multiclass Networks. Discret. Event Dyn. Syst. 13(1-2): 149-189 (2003) - [j17]Mike Chen, Charuhas Pandit, Sean P. Meyn:
In Search of Sensitivity in Network Optimization. Queueing Syst. Theory Appl. 44(4): 313-363 (2003) - [j16]Sean P. Meyn:
Sequencing and Routing in Multiclass Queueing Networks Part II: Workload Relaxations. SIAM J. Control. Optim. 42(1): 178-217 (2003) - [j15]Sanjay Shakkottai, R. Srikant, Sean P. Meyn:
Bounds on the throughput of congestion controllers in the presence of feedback delay. IEEE/ACM Trans. Netw. 11(6): 972-981 (2003) - [c6]Vladislav B. Tadic, Sean P. Meyn:
Asymptotic properties of two time-scale stochastic approximation algorithms with constant step sizes. ACC 2003: 4426-4431 - [c5]In-Koo Cho, Sean P. Meyn:
Dynamics of ancillary service prices in power distribution systems. CDC 2003: 2094-2099 - [c4]Vivek S. Borkar, Sean P. Meyn:
Value functions and performance evaluation in stochastic network models. CDC 2003: 2612-2617 - [c3]Vladislav B. Tadic, Sean P. Meyn, Roberto Tempo:
Randomized algorithms for semi-infinite programming problems. ECC 2003: 3011-3015 - 2002
- [j14]Vivek S. Borkar, Sean P. Meyn:
Risk-Sensitive Optimal Control for Markov Decision Processes with Monotone Cost. Math. Oper. Res. 27(1): 192-209 (2002) - 2001
- [j13]Sean P. Meyn:
Sequencing and Routing in Multiclass Queueing Networks Part I: Feedback Regulation. SIAM J. Control. Optim. 40(3): 741-776 (2001) - [c2]Sanjay Shakkottai, Rayadurgam Srikant, Sean P. Meyn:
Boundedness of utility function based congestion controllers in the presence of delay. CDC 2001: 616-621 - 2000
- [j12]Vivek S. Borkar, Sean P. Meyn:
The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning. SIAM J. Control. Optim. 38(2): 447-469 (2000)
1990 – 1999
- 1999
- [j11]Rong-Rong Chen, Sean P. Meyn:
Value iteration and optimization of multiclass queueing networks. Queueing Syst. Theory Appl. 32(1-3): 65-97 (1999) - [j10]Rayadurgam Ravikanth, Sean P. Meyn:
Bounds on achievable performance in the identification and adaptive control of time-varying systems. IEEE Trans. Autom. Control. 44(4): 670-682 (1999) - 1998
- [j9]Lyndon J. Brown, Sean P. Meyn, Robert A. Weber:
Adaptive dead-time compensation with application to a robotic welding system. IEEE Trans. Control. Syst. Technol. 6(3): 335-349 (1998) - 1997
- [j8]Douglas G. Down, Sean P. Meyn:
Piecewise linear test functions for stability and instability of queueing networks. Queueing Syst. Theory Appl. 27(3-4): 205-226 (1997) - [j7]Sean P. Meyn:
The policy iteration algorithm for average reward Markov decision processes with general state space. IEEE Trans. Autom. Control. 42(12): 1663-1680 (1997) - [c1]Shane G. Henderson, Sean P. Meyn:
Efficient Simulation of Multiclass Queueing Networks. WSC 1997: 216-223 - 1996
- [j6]Poornachandran Kumar, Sean P. Meyn:
Duality and linear programs for stability and performance analysis of queuing networks and scheduling policies. IEEE Trans. Autom. Control. 41(1): 4-17 (1996) - 1995
- [j5]Poornachandran Kumar, Sean P. Meyn:
Stability of queueing networks and scheduling policies. IEEE Trans. Autom. Control. 40(2): 251-260 (1995) - [j4]Douglas G. Down, Sean P. Meyn:
Stability of acyclic multiclass queueing networks. IEEE Trans. Autom. Control. 40(5): 916-919 (1995) - [j3]Jim G. Dai, Sean P. Meyn:
Stability and convergence of moments for multiclass queueing networks via fluid limit models. IEEE Trans. Autom. Control. 40(11): 1889-1904 (1995) - 1993
- [b1]Sean P. Meyn, Richard L. Tweedie:
Markov Chains and Stochastic Stability. Communications and Control Engineering Series, Springer 1993, ISBN 978-1-4471-3269-1, pp. 1-552 - [j2]Sean P. Meyn, Lyndon J. Brown:
Model reference adaptive control of time varying and stochastic systems. IEEE Trans. Autom. Control. 38(12): 1738-1753 (1993) - [j1]Sean P. Meyn, Michael R. Frater:
Recurrence times of buffer overflows in Jackson networks. IEEE Trans. Inf. Theory 39(1): 92-97 (1993)
Coauthor Index
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