Events Calendar

CS Colloquium: Wei Cheng (UCLA) - Integrating Multiple Networks for Big Data Analysis

Speaker: Wei Cheng, UCLA

Talk Title: Integrating Multiple Networks for Big Data Analysis

Series: CS Colloquium

Abstract: In many big data applications, data with complex structures can usually be modeled as network data. Usually, for one data mining problem, we have multiple networks. For one thing, data about the same object can be obtained from various. For another, the different objects may have complex structures and can be interrelated in a complex way. Integration of different network data is valuable for reaching a more accurate decision and discovering novel patterns. The task is challenging because of the inherent characteristics of the networks: 1) variety (e.g., complex structures, heterogeneous types and data sources); and 2) poor quality; 3) massive volume. In this talk, I will present our research efforts to use big data technologies to integrate multiple networks for both supervised and unsupervised data mining problems. First, I will begin by presenting the work of integrative analyzing multi-domain heterogeneous data for graph clustering. Next, I will present the work on robust sparse regression algorithm that integrates multi-source heterogeneous networks.

Biography: Wei Cheng is a Ph.D. candidate in Computer Science at University of North Carolina at Chapel Hill. He has been visiting Department of Computer Science of UCLA since 2013. He received a Master's and Bachelor's degree from Tsinghua University and Nanjing University, in 2010 and 2006, respectively. His research interests include big data, data mining, bioinformatics, computational biology, and machine learning. He is especially interested in scalable data analysis problems for data science with an emphasis on biological applications Previously, he also conducted research at Microsoft Research and IBM Research as an intern.

Host: Yan Liu

Location: Henry Salvatori Computer Science Center (SAL) - 213

Audiences: Everyone Is Invited

Contact: Assistant to CS chair