Talk Abstract: Graphs appear naturally in many applications. With ever increasing computing power available for scientific research, and popularity of online applications such as Facebook and Twitter, the size of graphs of interest increases exponentially with time. In this talk, we give a quick review of the state of the art for large graph visualization. We then focus on metric embedding/MDS, a technique for finding the layout of a graph with user-specified edge length, and discuss recent progress in this area. For the second part of the talk, we look at using map visualization to help explain results from machine learning algorithms, including recommender systems and word/name embeddings.
Speaker's Bio: Yifan Hu is a Senior Director of Research at Yahoo Research. Prior to joining Yahoo, he worked at AT&T Labs, Wolfram Research, and at Daresbury Laboratory. He received his B.S. and M.S. in applied mathematics from Shanghai Jiao-Tong University and Ph.D. in optimization from Loughborough University. His research interests include data mining, applied machine learning, and visualization.
This event is sponsored by Center for Data Science and Analytics. Prof. Nan Cao will introduce Yifan Hu.