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John N. Maidens
Person information
- affiliation: Ryerson University, Toronto, Ontario, Canada
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2020 – today
- 2020
- [j7]Ozan Ozyegen
, Sanaz Mohammadjafari
Experimental Results on the Impact of Memory in Neural Networks for Spectrum Prediction in Land Mobile Radio Bands. IEEE Trans. Cogn. Commun. Netw. 6(2): 771-782 (2020)
2010 – 2019
- 2019
- [c11]Karim El Mokhtari
Predicting Commentaries on a Financial Report with Recurrent Neural Networks. Canadian AI 2019: 531-542 - [c10]Sanaz Mohammadjafari, Emir Kavurmacioglu, John Maidens, Ayse Bener:
Neural Network Based Spectrum Prediction in Land Mobile Radio Bands for IoT deployments. IM 2019: 31-36 - 2018
- [j6]John Maidens
Symmetry reduction for dynamic programming. Autom. 97: 367-375 (2018) - [j5]John N. Maidens
Exploiting Symmetry for Discrete-Time Reachability Computations. IEEE Control. Syst. Lett. 2(2): 213-217 (2018) - [j4]John Maidens
Spatio-Temporally Constrained Reconstruction for Hyperpolarized Carbon-13 MRI Using Kinetic Models. IEEE Trans. Medical Imaging 37(12): 2603-2612 (2018) - [c9]Murat Arcak, John N. Maidens
Simulation-Based Reachability Analysis for Nonlinear Systems Using Componentwise Contraction Properties. Principles of Modeling 2018: 61-76 - [c8]Francis Palma, Tamer Abdou, Ayse Bener
An Improvement to Test Case Failure Prediction in the Context of Test Case Prioritization. PROMISE 2018: 80-89 - [i5]John N. Maidens, Murat Arcak:
Exploiting symmetry for discrete-time reachability computations. CoRR abs/1801.00516 (2018) - [i4]John N. Maidens, Axel Barrau, Silvère Bonnabel, Murat Arcak:
Symmetry reduction for dynamic programming. CoRR abs/1801.03237 (2018) - 2017
- [b1]John N. Maidens:
Optimal Control for Learning with Applications in Dynamic MRI. University of California, Berkeley, USA, 2017 - [c7]John N. Maidens
Symmetry reduction for dynamic programming and application to MRI. ACC 2017: 4625-4630 - [i3]Murat Arcak, John N. Maidens:
Simulation-based reachability analysis for nonlinear systems using componentwise contraction properties. CoRR abs/1709.06661 (2017) - 2016
- [j3]John N. Maidens
Optimizing Flip Angles for Metabolic Rate Estimation in Hyperpolarized Carbon-13 MRI. IEEE Trans. Medical Imaging 35(11): 2403-2412 (2016) - [c6]John N. Maidens
Semidefinite relaxations in optimal experiment design with application to substrate injection for hyperpolarized MRI. ACC 2016: 2023-2028 - [c5]John N. Maidens
Parallel dynamic programming for optimal experiment design in nonlinear systems. CDC 2016: 2894-2899 - 2015
- [j2]John N. Maidens
Reachability Analysis of Nonlinear Systems Using Matrix Measures. IEEE Trans. Autom. Control. 60(1): 265-270 (2015) - [c4]John N. Maidens
Optimal experiment design for physiological parameter estimation using hyperpolarized carbon-13 magnetic resonance imaging. ACC 2015: 5770-5775 - [i2]John N. Maidens, Murat Arcak:
A note on optimal experiment design for nonlinear systems using dynamic programming. CoRR abs/1503.07232 (2015) - [i1]John N. Maidens, Murat Arcak:
Semidefinite relaxations in optimal experiment design with application to substrate injection for hyperpolarized MRI. CoRR abs/1510.00455 (2015) - 2014
- [c3]John N. Maidens
Trajectory-based reachability analysis of switched nonlinear systems using matrix measures. CDC 2014: 6358-6364 - 2013
- [j1]John N. Maidens
Lagrangian methods for approximating the viability kernel in high-dimensional systems. Autom. 49(7): 2017-2029 (2013) - [c2]John N. Maidens
Global Lyapunov functions and a hierarchical control scheme for networks of robotic agents. ACC 2013: 4050-4055 - 2012
- [c1]Shahab Kaynama, John N. Maidens
Computing the viability kernel using maximal reachable sets. HSCC 2012: 55-64
Coauthor Index
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