The International Workshop on Dynamics, Nonlinearity, and Stochasticity
http://lxy.nwpu.edu.cn/info/1065/13244.htm
Xi’an, April 1-4, 2019 Seminar @ NWPU
Optimal stochasticity entails fractional calculus that enlightens big data and machine learning research
Prof. YangQuan Chen
MESA Lab of University of California, Merced
(E: ychen53@ucmerced.edu; W: http://mechatronics.ucmerced.edu)
Date/Time/Venue: April 2, 2019, Tuesday | Host: Professor Yong Xu
ABSTRACT:
This talk tries to connect stochasticity and fractional calculus in a generic sense. It has been widely experienced that randomness, when properly introduced, could enhance performance in optimization process, modeling and control etc. When asking what is the “optimal” randomness, in many cases, heavy-tailness (HT, or algebraic tail) emerges. A widely known example is the Levy flights used in population-based random search (e.g. Cuckoo search). Fractional calculus is shown to play an important role in characterizing HT processes. Thus the fractional order can be regarded as a tuning knob to achieve “optimal stochasticity”. In turn, we can say “optimal stochasticity” entails fractional calculus. In machine learning problems, optimal stochasticity may lead us to better than the best optimization performance. An illustrative example is given. For big data research, how to best quantify the variability leads us to the so-called “fractional-order data analytics (FODA)” using fractional calculus based methods. In summary, this talk attempts to convince the audience that whenever there is randomness, there is a chance to ask what is the optimal randomness, and in turn a chance to use fractional calculus.
BIOGRAPHY:
YangQuan Chen earned his Ph.D. from Nanyang Technological University, Singapore, in 1998. He had been a faculty of Electrical Engineering at Utah State University from 2000-12. He joined the School of Engineering, University of California, Merced in summer 2012 teaching “Mechatronics”, “Engineering Service Learning” and “Unmanned Aerial Systems” for undergraduates; “Fractional Order Mechanics” and “Nonlinear Controls” for graduates. His research interests include mechatronics for sustainability, cognitive process control, small multi-UAV based cooperative multi-spectral “personal remote sensing”, applied fractional calculus in controls, modeling and complex signal processing; distributed measurement and control of distributed parameter systems with mobile actuator and sensor networks.
Dr. Chen serves as a Co-Chair for IEEE Robotics and Automation Society Technical Committee (TC) on Unmanned Aerial Vehicle and Aerial Robotics (12-18). He recently served the TC Chair for the ASME DED Mechatronics Embedded Systems Applications (2009-10); Associated Editor (AE) for IEEE Trans. on Control Systems Technology (00-16), ISA Trans. (12-17), IFAC Control Engineering Practice (12-17), IET Control Theory and Applications (15-18) and Journal of Dynamics Systems, Measurements and Control (09-15). He now serves as Topic Editor-in-Chief of International Journal of Advanced Robotic Systems (Field Robotics), Section AE (Remote Sensors) for Sensors, Senior Editor for International Journal of Intelligent Robotic Systems, Topical AE for Nonlinear Dynamics (18-) and AE for IFAC Mechatronics, Intelligent Service Robotics, Energy Sources (Part A) (18-) and Fractional Calculus and Applied Analysis. He is a member of IEEE, ASME, AIAA, ASPRS, AUVSI and AMA. He relies on Google citation page to keep track of his publications at https://scholar.google.com/citations?user=RDEIRbcAAAAJ
Dr. Chen started some new investigations, published some papers and books, graduated some students, hosted some visiting scholars and also received some awards including the IFAC World Congress Best Journal Paper Award (Control Engineering Practice, 2011), First Place Awards for 2009 and 2011 AUVSI SUAS competitions, and most importantly, the “Relationship Counselor” award from IEEE Utah State University Student Branch for “explaining human relationship using control theory.” His is listed in Highly Cited Researchers by Clarivate in 2018.
Last updated 3/23/2019 by YangQuan Chen.
