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Joel A. Rosenfeld
Joel A. Rosenfeld
Assistant Professor, Department of Mathematics and Statistics, University of South Florida
Verified email at usf.edu - Homepage
Title
Cited by
Cited by
Year
Reinforcement Learning for Optimal Feedback Control: A Lyapunov-Based Approach
R Kamalapurkar, P Walters, J Rosenfeld, W Dixon
Springer, 2018
152*2018
Verification for Machine Learning, Autonomy, and Neural Networks Survey
W Xiang, P Musau, AA Wild, DM Lopez, N Hamilton, X Yang, J Rosenfeld, ...
arXiv preprint arXiv:1810.01989, 2018
1052018
Efficient model-based reinforcement learning for approximate online optimal control
R Kamalapurkar, JA Rosenfeld, WE Dixon
Automatica 74, 247-258, 2016
912016
Reachable set estimation and safety verification for piecewise linear systems with neural network controllers
W Xiang, HD Tran, JA Rosenfeld, TT Johnson
2018 Annual American Control Conference (ACC), 1574-1579, 2018
742018
Invariance-Like Results for Nonautonomous Switched Systems
R Kamalapurkar, JA Rosenfeld, A Parikh, AR Teel, WE Dixon
IEEE Transactions on Automatic Control 64 (2), 614-627, 2019
552019
Supporting lemmas for RISE-based control methods
R Kamalapurkar, JA Rosenfeld, J Klotz, RJ Downey, WE Dixon
arXiv preprint arXiv:1306.3432, 2013
492013
Decentralized formation control with connectivity maintenance and collision avoidance under limited and intermittent sensing
TH Cheng, Z Kan, JA Rosenfeld, WE Dixon
2014 American control conference, 3201-3206, 2014
422014
Approximate Dynamic Programming: Combining Regional and Local State Following Approximations
P Deptula, JA Rosenfeld, R Kamalapurkar, WE Dixon
IEEE transactions on neural networks and learning systems 29 (6), 2154-2166, 2018
312018
Dynamic Mode Decomposition for Continuous Time Systems with the Liouville Operator
JA Rosenfeld, R Kamalapurkar, L Gruss, TT Johnson
arXiv preprint arXiv:1910.03977, 2019
282019
The Occupation Kernel Method for Nonlinear System Identification
JA Rosenfeld, B Russo, R Kamalapurkar, TT Johnson
arXiv preprint arXiv:1909.11792, 2019
272019
Approximate Optimal Motion Planning to Avoid Unknown Moving Avoidance Regions
P Deptula, HY Chen, RA Licitra, JA Rosenfeld, WE Dixon
IEEE Transactions on Robotics 36 (2), 414-430, 2019
242019
Approximating the Caputo Fractional Derivative through the Mittag-Leffler Reproducing Kernel Hilbert Space and the Kernelized Adams--Bashforth--Moulton Method
JA Rosenfeld, WE Dixon
SIAM Journal on Numerical Analysis 55 (3), 1201-1217, 2017
242017
The Mittag Leffler reproducing kernel Hilbert spaces of entire and analytic functions
JA Rosenfeld, B Russo, WE Dixon
Journal of Mathematical Analysis and Applications 463 (2), 576-592, 2018
222018
Occupation Kernels and Densely Defined Liouville Operators for System Identification
JA Rosenfeld, R Kamalapurkar, B Russo, TT Johnson
2019 IEEE 58th Conference on Decision and Control (CDC), 6455-6460, 2019
212019
A mesh-free pseudospectral approach to estimating the fractional Laplacian via radial basis functions
JA Rosenfeld, SA Rosenfeld, WE Dixon
Journal of Computational Physics 390, 306-322, 2019
182019
Dynamic mode decomposition with control liouville operators
JA Rosenfeld, R Kamalapurkar
arXiv preprint arXiv:2101.02620, 2021
142021
State following (StaF) kernel functions for function approximation Part II: Adaptive dynamic programming
R Kamalapurkar, JA Rosenfeld, WE Dixon
2015 American Control Conference (ACC), 521-526, 2015
132015
The State Following Approximation Method
JA Rosenfeld, R Kamalapurkar, WE Dixon
IEEE transactions on neural networks and learning systems 30 (6), 1716-1730, 2018
122018
State following (StaF) kernel functions for function approximation Part I: Theory and motivation
JA Rosenfeld, R Kamalapurkar, WE Dixon
2015 American Control Conference (ACC), 1217-1222, 2015
112015
State following (StaF) kernel functions for function approximation Part I: Theory and motivation
JA Rosenfeld, R Kamalapurkar, WE Dixon
2015 American Control Conference (ACC), 1217-1222, 2015
112015
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