CIRSS Seminar: Jingrui He (Cancelled)

Abstract: Since its inception, crowd-sourcing has been used in a variety of applications such as crowdfunding, collective knowledge, collective creativity, and implicit crowdsourcing. In this talk, I will briefly introduce some machine learning and data mining techniques used in crowd-sourcing, including multiple imperfect labelers, classic learning, and unified learning. The talk will cover the following papers:

1. Victor Sheng, et al., Get another label? Improving Data Quality and Data Mining using Multiple, Noisy Labelers. KDD 09
2. Christopher Lin, et al., To Re(label), or Not To Re(label). HCOMP 14
3. Yan Yan, et al., Active Learning from Crowds. ICML 11
4. Christopher Lin, et al., Re-active Learning: Active Learning with Relabeling. AAAI 16
5. Nagarajan Natarajan, et al., Learning with Noisy Labels. NeurIPS 13
6. Vikas Raykar, et al., Learning from Crowds. JMLR 10
7. Yao Zhou, et al., MultiC2: an Optimization Framework for Learning from Task and Worker Dual Heterogeneity. SDM 17
8. Yao Zhou, et al., A Randomized Approach for Crowdsourcing in the Presence of Multiple Views. ICDM 17

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, 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 has served on the 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).