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CIRSS Seminar - Exploring Rare Categories on Graphs: Local vs. Global


Friday, November 13, 2020
4pm - 5pm

Zoom

Event Details

Session leaders: Jingrui He, iSchool Associate Professor
Description: Rare categories refer to the under-represented minority classes in imbalanced data sets. They are prevalent across many high-impact applications in the security domain where the input data can be represented as graphs. In this talk, I will focus on two complementary strategies for exploring such rare categories -- local vs. global. With the local strategy, the goal is to explore a small neighborhood around a seed node from the rare category for identifying additional rare examples; with the global strategy, the goal is to explore the entire graph in order to identify rare category oriented representations. For each strategy, I will introduce recent techniques proposed from iSAIL Lab (https://isail-laboratory.github.io). Towards the end, I will also discuss potential future directions on this topic.

Bio:
Jingrui He is an associate professor in the School of Information Sciences at the University of Illinois at Urbana-Champaign. She received her PhD in machine learning from Carnegie Mellon University in 2010. Her research focuses on heterogeneous machine learning, rare category analysis, active learning and semi-supervised learning, with applications in social network analysis, healthcare, finance, and manufacturing processes. She is the recipient of the 2016 NSF CAREER Award and a three-time recipient of the IBM Faculty Award, in 2018, 2015 and 2014 respectively, and was selected for an IJCAI 2017 Early Career Spotlight. He has published more than 100 refereed articles, and is the author of two books (Analysis of Rare Categories, Springer-Verlag, 2011; Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective, CRC Taylor and Francis Group, 2020). Her papers have been selected as "Best of the Conference" by ICDM 2016, ICDM 2010, and SDM 2010. She is the Associate Editor of ACM Transactions on Knowledge Discovery from Data (TKDD), and the Action Editor of Data Mining and Knowledge Discovery. She has served on the area chair/senior program committee/program committee for Knowledge Discovery and Data Mining (KDD), International Joint Conference on Artificial Intelligence (IJCAI), Association for the Advancement of Artificial Intelligence (AAAI), SIAM International Conference on Data Mining (SDM), and International Conference on Machine Learning (ICML).