AboutI am an assistant professor in the Computing and Mathematical Sciences department at the California Institute of Technology.
New PhD ProgramProspective PhD Students, please consider applying to Caltech's new PhD program in Computing and Mathematical Sciences.
I also recruit from the PhD program in Computation & Neural Systems.
ResearchMy research interests lie primarily in the theory and application of statistical machine learning. I am more generally interested in artificial intelligence. I also interact closely with the RSRG group at Caltech.
Currently, I am particularly interested in learning with humans in the loop, interactive learning systems, and spatiotemporal reasoning. In the past, my research has been applied to information retrieval, recommender systems, text classification, learning from rich user interfaces, analyzing implicit human feedback, data-driven animation, sports analytics, policy learning in robotics, and adaptive routing & allocation problems.
- Learning Fine-Grained Spatial Models for Dynamic Sports Play Prediction
Yisong Yue, Patrick Lucey, Peter Carr, Alina Bialkowski, Iain Matthews
IEEE International Conference on Data Mining (ICDM), December, 2014.
(Best Paper Nomination)
- Personalized Collaborative Clustering
Yisong Yue, Chong Wang, Khalid El-Arini, Carlos Guestrin
International World Wide Web Conference (WWW), April, 2014.
- Linear Submodular Bandits and their Application to Diversified Retrieval
Yisong Yue, Carlos Guestrin
Neural Information Processing Systems (NIPS), December, 2011.
- Beat the Mean Bandit
Yisong Yue, Thorsten Joachims
International Conference on Machine Learning (ICML), June, 2011.
- Predicting Structured Objects with Support Vector Machines
Thorsten Joachims, Thomas Hofmann, Yisong Yue, Chun-Nam Yu
Communications of the ACM (CACM), Research Highlight, 52(11), 97--104, November, 2009.
(With a technical perspective by John Shawe-Taylor.)
News & Announcements
- Interview by Jessica Stoller-Conrad @Caltech. [link]
- Invited talk at Human Propelled Machine Learning Workshop at NIPS 2014.
- Learning Fine-Grained Spatial Models for Dynamic Sports Play Prediction accepted for publication at ICDM 2014. [pdf][demo][press release]
- Personalization Workshop: Please consider participating in our Personalization Workshop being held at NIPS 2014!
- Sports Analytics Workshop: Please consider participating in our Large-Scale Sports Analytics Workshop being held at KDD 2014!
- Personalized Collaborative Clustering accepted for publication at WWW 2014. [pdf][slides][data]
- Invited talk at DISCML Workshop at NIPS 2013.