- 0822M10 / Dr. 이수민 / A Tutorial on First Order Distributed Optimization Methods
- Date2016-10-20 11:27:18
A Tutorial on First Order Distributed Optimization Methods
이수민 (Post doctoral Fellow, Georgia Instituete of Technology)
Aug. 22 (Mon) 10:00 / Building 133 Room 316-1
Due to the advent of internet, smart devices, and communication means like social networking sites, the amount of data produced by mankind is growing rapidly every year. Though all this information produced can be extremely useful and meaningful when processed, current technology is not mature enough to efficiently and intelligently analyze the generated data. This in turn leads to growing interests in distributed data processing techniques. In this talk, I will present two distributed optimization algorithms which can efficiently process the data on decentralized network systems and cluster of computers operated by Hadoop and Spark. Applications of the algorithms on decentralized estimation in robot networks and health insurance claim denial prediction will be discussed as well.
Dr. Soomin Lee is a research faculty member in Industrial and Systems Engineering at Georgia Tech and a recipient of the NSF Fellowship Program for Enhancing Partnership with Industry. She received her Ph.D. in Electrical and Computer Engineering from the University of Illinois, Urbana-Champaign (2013). After the graduation, she worked as a postdoc associate in Duke Robotics Group. She also received two master's degrees from the Korea Advanced Institute of Science and Technology in Electrical Engineering, and from the University of Illinois at Urbana-Champaign in Computer Science. In 2009, she was an assistant research officer at the Advanced Digital Science Center (ADSC) in Singapore. Her research interests include theoretical optimization, control and optimization of various distributed engineering systems interconnected over complex networks, and large-scale machine learning for big data analytics in healthcare.