AboutI am an assistant professor in the Computing and Mathematical Sciences department at the California Institute of Technology. I am the director of the DOLCIT, which is centered around research pertaining statistical decision theory, statistical machine learning, and optimization, broadly construed.
Tenure-Track Faculty OpeningThe Computing and Mathematical Sciences (CMS) Department at Caltech invites applications for tenure-track faculty positions. See details here.
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 am the director of DOLCIT, and I also interact closely with the RSRG and Computational Vision groups at Caltech.
Currently, I am particularly interested in learning with humans in the loop, interactive learning systems, structured prediction, 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.
Some Recent Publications:
- A Decision Tree Framework for Spatiotemporal Sequence Prediction
Taehwan Kim, Yisong Yue, Sarah Taylor, Iain Matthews
ACM Conference on Knowledge Discovery and Data Mining (KDD), August, 2015.
- 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.
- Learning Policies for Contextual Submodular Prediction
Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, J. Andrew Bagnell
International Conference on Machine Learning (ICML), June, 2013.
- Large Scale Validation and Analysis of Interleaved Search Evaluation
Olivier Chapelle, Thorsten Joachims, Filip Radlinski, Yisong Yue
ACM Transactions on Information Systems (TOIS), 30(1), 6:1--6:41, February, 2012.
(Selected for ACM Notable Computing Books and Articles of 2012)
News & Announcements
- Blog Post: Thoughts on NIPS 2015 and OpenAI.
- Invited Workshop: Algorithms for Human Robot Interaction Workshop.
- Blog Post: Thoughts on KDD 2015.
- Fundraising Chair of AISTATS 2016.
- Invited Talk at Reflections | Projections 2015 organized by ACM@UIUC.
- Invited Workshop: Data-driven Algorithmics Workshop. [slides]
- A Decision Tree Framework for Spatiotemporal Sequence Prediction accepted for publication at KDD 2015. [pdf][demo]
- Sports Analytics Workshop: Please consider participating in our Large-Scale Sports Analytics Workshop being held at KDD 2015!
- 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]