Distributed Algorithms for Solving Large Linear Equations and Applications
报告题目: Distributed Algorithms for Solving Large Linear Equations and Applications

Each agent only knows part of the overall equation and can communicate with its nearby
neighbors. A distributed algorithm is devised to enable all agents to achieve exponentially
fast a common solution. The proposed algorithm is distributed, works for all linear equations
as long as the solution exists, does not involve any sufficiently small step size, and works
asynchronously. Further improvement to the algorithm is also discussed including utilization
the sparsity to reduce the state dimension, elimination of the initialization step, and
generalization to achieving least square solutions. Applications of the algorithm includes
large content delivery across vehicular networks, distributed  network localizations, and so on.​

and Astronautics at Purdue University since August 2015. He received his bachelor and master
degree in Harbin Institute of Technology in 2006 and 2008, respectively. He completed his
Ph.D. study at Prof. A. Stephen Morse’s group in Electrical Engineering at Yale University in 2014.
Then he worked as a post-doc at MIT for a year.  During his Ph. D. study, he held a position of
visiting scholar at Australian National University and worked part-time for Yale Law School.
He has received the Yale University Raymond John Wean Fellowship (2009) and the Chinese
Government Award for Outstanding Students Abroad (2014). His research interests include
distributed algorithms and control, multi-agent networks, formation control, and collaborations
of UAVs.​