王钢教授
Gang Wang is currently a Professor with the School of Automation, Beijing Institute of Technology, Beijing, China. He received his B.Eng. degree in electrical engineering and automation from the Beijing Institute of Technology, Beijing, China, in 2011, and the Ph.D. degree in electrical engineering from the University of Minnesota, Minneapolis, MN, USA, in 2018, where he stayed as a postdoctoral associate until 2020. He received a number of awards, including the Best Paper Award from the Springer Journal Frontiers of Information Technology & Electronic Engineering (FITEE, flagship journal of the Chinese Academy of Engineering) in 2021, the Excellent Doctoral Dissertation Award from the Chinese Association of Automation in 2020, the IEEE Power & Energy Society General Meeting (PES-GM) in 2019, as well as the European Signal Processing Conference (Eusipco) in 2017. He is currently on the editorial board of Signal Processing.
E-mail: gangwang@mylpg.net
Work: +86 10 68917912
EDUCATION
• University of Minnesota, Minneapolis, MN, United States
Ph.D. in Electrical and Computer Engineering, Feb. 2015—Apr. 2018
Advisor: Prof. Georgios B. Giannakis (IEEE/EURASIP Fellow)
• Beijing Institute of Technology, Beijing, China
Ph.D. in Automatic Control, Sep. 2011—Mar. 2015
Advisor: Prof. Jie Chen (IEEE/IFAC Fellow)
• Beijing Institute of Technology, Beijing, China
B. Eng. in Automatic Control, Sep. 2007—Jun. 2011
Advisor: Prof. Jian Sun
RESEARCH INTERESTS
Algorithms, analysis, and applications of control, optimization, and reinforcement learning (RL) to Multi-Agent Networks and Cyber-Physical Systems. Experience, background, and current research include data-driven control under cyberattacks, distributionally robust optimization and learning, power system dynamics, and finite-time analysis of multi-agent RL algorithms.
PUBLICATIONS
Published 35 journal papers in e.g. IEEE TIT/TAC/TSP/TCNS; and 35 conference papers in e.g. NeurIPS/AISTAS/ICASSP.
Total citations: ~1,600, h-index: 21.
Google scholar: http://scholar.google.com/citations?user=4MPZS5wAAAAJ&hl=en
Book Chapters
[B1] A. Sadeghi, G. B. Giannakis, G. Wang, and F. Sheikholeslami, Reinforcement Learning for Caching with Space-Time Popularity Dynamics. Edge Caching for Mobile Networks, V. Poor and W. Chen Editors, to appear October 2021.
[B2] V. Kekatos, G. Wang, H. Zhu, and G. B. Giannakis, PSSE Redux: Convex Relaxation, Decentralized, Robust, and Dynamic Approaches. Advances in Power System State Estimation, M. El-Hawary Editor, December 2020.
Submitted Papers
[S1] W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen, “Data-Driven Resilient Model Predictive Control under Denial-of-Service,” IEEE Transactions on Automatic Control, pp. 1-13, revised August 2021.
[S2] A. Sadeghi, G. Wang, and G. B. Giannakis, “Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data,” IEEE Transactions on Signal Processing, pp. 1-12, revised August 2021.
[S3] X. Wang, J. Sun, J. Berberich, G. Wang, F. Allgower, and J. Chen, “Data-driven Control of Dynamic Event-triggered Systems with Delays,” IEEE Transactions on Automatic Control, pp. 1-13, submitted May 2021.
[S4] G. Wang, B. Li, and G. B. Giannakis, “A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation,” IEEE Transactions on Automatic Control, pp. 1-12, submitted March 2020.
Refereed Journal Papers
[J1] W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen,“Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol,”IEEE Transactions on Automatic Control, pp. 1-13, to appear Aug. 2022.
[J2] X. Wang, J. Sun, G. Wang, and L. Dou,“A Mixed Switching Event-triggered Transmission Scheme for Networked Control Systems,” IEEE Transactions on Control of Network Systems, pp. 1-12, to appear Dec. 2021.
[J3] W. Liu, J. Sun, G. Wang, and J. Chen,“Quantized Impulsive Control of Linear Systems under Bounded Disturbances and DoS Attacks,” IEEE Transactions on Control of Network Systems, pp. 1-12, to appear December 2021.
[J4] X. Zhang, G. Wang, T. Cai, and J. Sun,“Network Topology Identification under the Multi-agent Agreement Protocol," Journal of the Franklin Institute, pp. 1-10, to appear Sept. 2021.
[J5] Y. Xu, J. Sun, and G. Wang, “Dynamic Triggering Mechanisms for Distributed Adaptive Synchronization Control and Its Application to Circuit Systems,” IEEE Transactions on Circuits and Systems–I: Regular Papers, pp. 1-10, to appear 2021.
[J2] G. Wu, G. Wang, J. Sun, and J. Chen,“Optimal Partial Feedback Attacks in Cyber-Physical Power Systems,”IEEE Transactions on Automatic Control, vol. 65, no. 9, pp. 3919-3926, Sept. 2020.
[J3] G. Wu, G. Wang, J. Sun, and L. Xiong, “Optimal Switching Data Injection Attacks and Countermeasures in Cyber-Physical Systems,”IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1-10, to appear 2019.
[J4] G. Wu, H. Xiong, G. Wang, and J. Sun, “Linear Quadratic Regulator of Discrete-time Switched Linear Systems,”IEEE Transactions on Circuits and Systems–II: Express Briefs, to appear 2020.
[J5] Q. Yang, G. Wang, A. Sadeghi, G. B. Giannakis, and J. Sun, “Two-Timescale Voltage Control in Distribution Grids using Deep Reinforcement Learning,” IEEE Transactions on Smart Grid, vol. 11, no. 3, pp. 2313-2323, May 2020.
[J6] Q. Zhao, J. Sun, G. Wang, and J. Chen, “Event-Triggered ADP for Nonzero-Sum Games of Unknown Nonlinear Systems,” IEEE Transactions on Neural Networks and Learning Systems, to appear 2021.
[J7] Y. Xu, J. Sun, Z.-G. Wu, and G. Wang, “Fully Distributed Adaptive Event-Triggered Control of Networked Systems with Actuator Bias Faults,” IEEE Transactions on Cybernetics, to appear 2021.
[J8] Q. Yang, A. Sadeghi, G. Wang, and J. Sun, “Learning Two-layer ReLU Networks is as Nearly Easy as Learning Linear Classifiers on Separable Data,” IEEE Transactions on Signal Processing, vol. 69, pp. 4416-4427, July 021.
[J9] G. Wu, G. Wang, J. Sun, and J. Chen, “Optimal Partial Feedback Attacks in Cyber-Physical Power Systems,” IEEE Transactions on Automatic Control, vol. 65, no. 9, pp. 3919-3926, Sept. 2020.
[J10] G. Wu, G. Wang, J. Sun, and L. Xiong “Optimal Switching Data Injection Attacks and Countermeasures in Cyber-Physical Systems,” IEEE Trans. Systems, Man, and Cybernetics: Systems, vol. 51, no. 8, pp. 4825-4835, Aug. 2021.
[J11] Q. Yang, G. Wang, A. Sadeghi, G. B. Giannakis, and J. Sun, “Two-Timescale Voltage Control in Distribution Grids using Deep Reinforcement Learning,” IEEE Transactions on Smart Grid, vol. 11, no. 3, pp. 2313-2323, May 2020.
[J12] G. Wang, H. Zhu, G. B. Giannakis, and J. Sun, “Robust Power System State Estimation from Rank-One Measurements,” IEEE Transactions on Control of Network Systems, vol. 6, no. 4, pp. 1391-1403, December 2019.
[J13] A. Sadeghi, G. Wang, and G. B. Giannakis, “Deep Reinforcement Learning for Adaptive Caching in Hierarchical Content Delivery Networks,” IEEE Transactions on Cognitive Communications and Networking, vol. 5, no. 4, pp. 1024-1033, Dec. 2019.
[J14] G. Wang, G. B. Giannakis, and J. Chen, “Robust and Scalable Power System State Estimation using Composite Optimization,” IEEE Transactions on Smart Grid, vol. 10, no. 6, pp. 6137-6147, November 2019.
[J15] M. Xiong, Q. Liu, G. Wang, G. B. Giannakis, and C. Huang, “Resonant Beam Communications: Principles and Designs,” IEEE Communications Magazine, vol. 57, no. 10, pp. 34-39, October 2019.
[J16] Q. Zhang, G. Wang, J. Chen, G. B. Giannakis, and Q. Liu, “Mobile Energy Transfer in Internet of Things,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 9012-9019, October 2019.
[J17] L. Zhang, G. Wang, and G. B. Giannakis, “Real-time Power System State Estimation and Forecasting via Deep Unrolled Neural Networks,” IEEE Transactions on Signal Processing, vol. 67, no. 15, pp. 4069-4077, August 2019.
[J18] J. Chen, G. Wang, and G. B. Giannakis, “Graph Multiview Canonical Correlation Analysis,” IEEE Transactions on Signal Processing, vol. 67, no. 11, pp. 2826-2838, June 2019.
[J19] G. Wang, G. B. Giannakis, and J. Chen, “Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization,” IEEE Transactions on Signal Processing, vol. 67, no. 9, pp. 2357-2370, May 2019.
[J20] J. Chen, G. Wang, and G. B. Giannakis, “Nonlinear Dimensionality Reduction for Discriminative Analytics of Multiple Datasets,” IEEE Transactions on Signal Processing, vol. 67, no. 3, pp. 740-752, February 2019.
[J21] G. Wang, G. B. Giannakis, J. Chen, and J. Sun, “Distribution System State Estimation: An Overview of Recent Developments,” Springer Frontiers of Information Technology & Electronic Engineering, vol. 20, no. 1, pp. 4-17, January 2019.
[J22] J. Chen, G. Wang, Y. Shen, and G. B. Giannakis, “Canonical Correlation Analysis of Datasets with a Common Source Graph,” IEEE Transactions on Signal Processing, vol. 66, no. 16, pp. 4398-4408, August 2018.
[J23] G. Wang, G. B. Giannakis, Y. Saad, and J. Chen, “Phase Retrieval via Reweighted Amplitude Flow,” IEEE Transactions on Signal Processing, vol. 66, no. 11, pp. 2818-2833, June 2018.
[J24] G. Wang, A. S. Zamzam, G. B. Giannakis, and N. D. Sidiropoulos, “Power System State Estimation via Feasible Point Pursuit: Algorithms and Cramer-Rao Bound,” IEEE Transactions on Signal Processing, vol. 66, no. 6, pp. 1649-1658, March 2018.
[J25] G. Wang, G. B. Giannakis, and Y. C. Eldar, “Solving Random Systems of Quadratic Equations via Truncated Amplitude Flow,” IEEE Transactions on Information Theory, vol. 64, no. 2, pp. 773-794, February 2018.
[J26] G. Wang, L. Zhang, G. B. Giannakis, M. Akcakaya, and J. Chen, “Sparse Phase Retrieval via Truncated Amplitude Flow,” IEEE Transactions on Signal Processing, vol. 66, no. 2, pp. 479-491, January 2018.
[J27] L. Zhang, G. Wang, D. Romero, and G. B. Giannakis, “Randomized Block Frank-Wolfe for Convergent Large-Scale Learning,” IEEE Transactions on Signal Processing, vol. 65, no. 24, pp. 6448-6461, December 2017.
[J28] G. Wang, G. B. Giannakis, and J. Chen, “Scalable Solvers of Random Quadratic Equations via Stochastic Truncated Amplitude Flow,” IEEE Transactions on Signal Processing, vol. 65, no. 5, pp. 1961–1974, March 2017.
[J29] G. Wang, V. Kekatos, A. J. Conejo, and G. B. Giannakis, “Ergodic Energy Management Leveraging Resource Variability in Distribution Grids,” IEEE Transactions on Power Systems, vol. 31, no. 6, pp. 4765-4775, Nov. 2016.
[J30] J. Chen, G. Wang, and J. Sun, “Power Scheduling for Kalman Filtering over Lossy Wireless Sensor Networks,” IET on Control Theory & Applications, vol. 11, no. 4, pp. 531-540, February 2016.
[J31] V. Kekatos, G. Wang, A. J. Conejo, and G. B. Giannakis, “Stochastic Reactive Power Management in Microgrids with Renewables,” IEEE Transactions on Power Systems, vol. 30, no. 6, pp. 3386-3395, November 2015.
[J32] G. Wang, J. Chen, and J. Sun, “Stochastic Stability of Extended Filtering for Nonlinear Systems with Measurement Packet Losses,” IET Control Theory & Applications, vol. 7, no. 17, pp. 2048-2055, Nov. 2013.
Conference Papers
[C1] Z. Chen, W. Zhang, J. Yan, G. Wang, and J.-Y. Wang, “Learning Dual Dynamic Representations on Time-Sliced User-Item Interaction Graphs for Sequential Recommendation,” ACM Intl. Conf. on Information and Knowledge Management (CIKM), Turin, Italy, October 22-26, 2021.
[C2] G. Wang, S. Lu, G. B. Giannakis, G. Tesauro, and J. Sun, “Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis,” Proc. of Neural Information Processing Systems, Vancouver, Canada, December 6-12, 2020. (Acceptance rate: 20%)
[C3] Q. Yang, A. Sadeghi, G. Wang, G. B. Giannakis, and J. Sun, “Deep Policy Gradient for Reactive Power Control in Distribution Systems,” Proc. of SmartGridCom, Tempe, AZ, USA, October 6-9, 2020.
[C4] Q. Yang, A. Sadeghi, G. Wang, G. B. Giannakis, and J. Sun, “Graph Convolutional Networks for Power System State Estimation,” Proc. of SmartGridCom, Tempe, AZ, USA, October 6-9, 2020.
[C5] G. Wang and G. B. Giannakis, “Finite-Time Error Bounds for Biased Stochastic Approximation Algorithms with Applications to Q-Learning,” Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Palermo, Sicily, Italy, June 3-5, 2020.
[C6] J. Sun, G. Wang, G. B. Giannakis, Q. Yang, and Z. Yang, “Finite-Sample Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation,” Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Palermo, Sicily, Italy, June 3-5, 2020.
[C7] A. Sadeghi, G. Wang, and G. B. Giannakis, “Hierarchical Caching via Deep Reinforcement Learning,” Proc. of Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 4-9, 2020.
[C8] Q. Yang, M. Coutino, G. Wang, G. B. Giannakis, and G. Leus, “Learning Connectivity and High-Order Interactions Radial Distribution Grids,” Proc. of Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 4-9, 2020.
[C9] Q. Yang, G. Wang, A. Sadeghi, G. B. Giannakis, and J. Sun, “Two-Timescale Voltage Regulation in Distribution Grids Using Deep Reinforcement Learning,” IEEE Intl. Conf. on Commun., Control, and Computing Technology for Smart Grids (SmartGridComm), Beijing, China, October 21-24, 2019.
[C10] G. Wang, G. B. Giannakis, and J. Chen, “Fast LAV Estimation via Composite Optimization,” IEEE Power & Energy Society General Meeting (PES-GM), Atlanta, GA, August 4-8, 2019.— Selected as one of the Best Conference Papers
[C11] L. Zhang, G. Wang, and G. B. Giannakis, “Distribution System State Estimation Using Data- and Physics-Driven Deep Neural Networks,” IEEE Data Science Workshop (DSW), Minneapolis, MN, June 2-5, 2019.
[C12] J. Chen, G. Wang, and G. B. Giannakis, “Multiview Canonical Correlation Analysis over Graphs,” Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 12-17, 2019.
[C13] L. Zhang, G. Wang, and G. B. Giannakis, “Power System State Forecasting via Deep Recurrent Neural Networks,” Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 12-17, 2019.
[C14] L. Zhang, G. Wang, and G. B. Giannakis, “Real-time Power System State Estimation via Deep Unrolled Neural Networks,” Globalsip, Anaheim, CA, USA, Nov. 26-28, 2018.
[C15] J. Chen, G. Wang, and G. B. Giannakis, “Nonlinear Discriminative Dimensionality Reduction of Multiple Datasets,” Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Oct. 28-31, 2018.
[C16] G. Wang, L. Zhang, G. B. Giannakis, and J. Chen, “Sparse Phase Retrieval via Iteratively Reweighted Amplitude Flow,” EUSIPCO, Rome, Italy, September 3-7, 2018.
[C17] J. Chen, G. Wang, Y. Shen, and G. B. Giannakis, “Canonical Correlation Analysis with Common Graph Priors,” IEEE Statistical Signal Process. Wksp., Freiburg, Germany, June 10-13, 2018.
[C18] G. Wang, J. Chen, and G. B. Giannakis, “DPCA: Dimensionality Reduction for Discriminative Analytics of Multiple Large-Scale Datasets,” Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 15-20, 2018.
[C19] L. Zhang, G. Wang, and G. B. Giannakis, “Going Beyond Linear Dependencies to Unveil Connectivity of Meshed Grids,” IEEE Wksp. on Comput. Advances in Multi-Sensor Adaptive Processing (CAMSAP), Curacao, Dutch Antilles, December 10-13, 2017.
[C20] G. Wang, G. B. Giannakis, Y. Saad, and J. Chen, “Solving Most Systems of Random Quadratic Equations,” Neural Information Process. Systems (NeurIPS), Long Beach, USA, Dec. 4-9, 2017. (Acceptance rate: 21%)
[C21] G. Wang, G. B. Giannakis, and J. Chen, “Solving Large-scale Systems of Random Quadratic Equations via Stochastic Truncated Amplitude Flow,” European Signal Processing Conference (EUSIPCO), Kos Island, Greece, August 28-September 3, 2017. (Received the Best Student Paper Award)
[C22] G. Wang, G. Giannakis, J. Chen, and M. Akcakaya, “SPARTA: Sparse Phase Retrieval via Truncated Amplitude Flow,” Intl. Conf. on Acoustics, Speech, and Signal Process. (ICASSP), New Orleans, LA, Mar. 5-9, 2017.
[C23] G. Wang and G. B. Giannakis, “Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow,” Neural Information Processing Systems (NeurIPS), Barcelona, Spain, December 5-10, 2016. (Acceptance rate: 22.72%)
[C24] G. Wang, A. S. Zamzam, G. B. Giannakis, and N. D. Sidiropoulos, “Power System State Estimation via Feasible Point Pursuit,” IEEE Global Conf. on Signal and Information Processing (GlobalSIP), Washington, DC, December 7-9, 2016.
[C25] B. Yang, G. Wang, and N. D. Sidiropoulos, “Tensor completion via group-sparse regularization,” Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, November 6-9, 2016.
[C26] G. Wang, V. Kekatos, and G. B. Giannakis, “Stochastic Energy Management in Distribution Grids,” IEEE Intl. Conf. on Acoustics, Speech, and Signal Process. (ICASSP), Shanghai, China, March 20-25, 2016.
[C27] V. Kekatos, G. Wang, A. J. Conejo, and G. Giannakis, “Stochastic Reactive Power Management in Microgrids with Renewables,” IEEE Power & Energy Society General Meeting (PES-GM), Denver, CO, July 26-30, 2015.
[C28] D. Berberidis, V. Kekatos, G. Wang, and G. B. Giannakis, “Online Censoring for Large-Scale Regression,” Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, Australia, April 19-24, 2015.
[C29] G. Wang, D. Berberidis, V. Kekatos, and G. Giannakis, “Online Reconstruction from Big Data via Compressive Censoring,” IEEE Global Conf. on Signal and Inf. Process. (GlobalSIP), Atlanta, GA, December 3-5, 2014.
[C30] D. K. Berberidis, G. Wang, V. Kekatos, and G. B. Giannakis, “Adaptive Censoring for Large-Scale Regressions,” Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, November 2-5, 2014.
[C31] V. Kekatos, G. Wang, and G. B. Giannakis, “Stochastic Loss Minimization for Power Distribution Networks,” North America Power Systems (NAPS), Pullman, WA, September 7-9, 2014.
[C32] G. Wang, S.-J. Kim, and G. B. Giannakis, “Moving-horizon Dynamic Power System State Estimation Using Semidefinite Relaxation,” IEEE Power & Energy Society General Meeting (PES-GM), Washington, DC, July 27-31, 2014.
[C33] S.-J. Kim, G. Wang, and G. B. Giannakis, “Online Semidefinite Programming for Power System State Estimation,” Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), Florence, Italy, May 4-9, 2014.
[C34] G. Wang, J. Chen, and J. Sun, “On Sequential Kalman Filtering with Scheduled Measurements,” IEEE Conf. on Cyber Technology in Automation, Control and Intelligent Systems, Nanjing, May 26-30, 2013.
[C35] Z. Zhuang, G. Wang, Y. Travadi, and J. Sun, “Phase Retrieval via Second-Order Nonsmooth Optimization,” Intl. Conf. on Machine Learning (ICML) Wksp. on Beyond First-order Methods, July 13-17, 2020.
[C36] G. Wang and G. B. Giannakis, “TGGF: Truncated Generalized Gradient Flow for Solving Random Systems of Quadratic Equations,” Intl. Conf. on Machine Learning (ICML) Wksp. on Nonconvex Optimization, New York City, June 19-25, 2016.
PROFESSIONAL SERVICE
Editorship
Associate Editor, Signal Processing (Elsevier), Sept. 2019---Present (IF: 4.1)
Program Committee
• 2020-2021 International Conference on Learning Representations (ICLR)
• 2019-2021 AAAI Conference on Artificial Intelligence (AAAI)
• 2019-2021 Neural Information Processing Systems (NeurIPS)
• 2019-2021 International Conference on Machine Learning (ICML)
• 2019 IEEE Data Science Workshop (DSW)
• 2019 IEEE Intl. Conf. on Wireless Communications and Signal Processing (WCSP)
• 2019 IEEE Intl. Wksp. on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Reviewer for Journals
The Mathematical Reviews of American Mathematical Society
IEEE Transactions on Information Theory, IEEE Transactions on Automatic Control, IEEE Transactions on Signal Processing, IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, IEEE Transactions on Signal and Information Processing over Networks, IEEE Journal of Selected Topics in Signal Processing, IEEE Transactions on Neural Networks and Learning Systems, IEEE/ACM Transactions on Networking, IEEE Transactions on Cognitive Communications and Networking, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Sustainable Energy, IEEE Transactions on Aerospace and Electronic Systems, IEEE Transactions on Energy Conversion, IEEE Access, IEEE Internet of Things Journal, IEEE/CAA J. of Automatica Sinica, IEEE Control System Letters, IEEE Power Engineering Letters, IEEE Signal Processing Letters, Springer Journal on Scientific Computing, Intl. J. of Electrical Power & Energy Systems, Energies, IET Generation, Transmission & Distribution, Optimization Methods & Software, Neurocomputing, Pattern Recognition, Heliyon
Reviewer for Conferences
Neural Information Processing Systems, Intl. Conf. on Machine Learning, Conf. on Learning Theory, IEEE Intl. Conf. on Acoustics, Speech and Signal Processing, American Control Conference, IEEE Conf. on Control and Decision, IEEE Statistical Signal Processing Workshop, IEEE Intl. Workshop on Computational Advances in Multi-Sensor Adaptive Processing, IEEE Power & Energy Society General Meeting, IEEE Data Science Workshop, IEEE Conf. on Automation Science and Engineering, Chinese Control Conference