Yisong Yue
California Institute of Technology
1200 E. California Blvd.
CMS, 305-16
Pasadena, CA 91125

Office: 303 Annenberg
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Admin: Diane Goodfellow (

I 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 broadly centered around research pertaining statistical decision theory, statistical machine learning, and optimization.
New PhD Program
Prospective 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.
My 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, as well as the Center for Autonomous Systems and Technology (CAST) and the Center for the Mathematics of Information (CMI).

My research interests lie primarily in the theory and application of statistical machine learning. I am particularly interested in developing novel methods for interactive machine learning and structured prediction. 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, behavior analysis, sports analytics, policy learning in robotics, and adaptive planning & allocation problems.
Selected Recent Publications:
  • Near-Optimal Machine Teaching via Explanatory Teaching Sets
    Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue
    International Conference on Artificial Intelligence and Statistics (AISTATS), April 2018.
  • Multi-dueling Bandits with Dependent Arms
    Yanan Sui, Vincent Zhuang, Joel Burdick, Yisong Yue
    Conference on Uncertainty in Artificial Intelligence (UAI), August 2017.
  • Coordinated Multi-Agent Imitation Learning
    Hoang M. Le, Yisong Yue, Peter Carr, Patrick Lucey
    International Conference on Machine Learning (ICML), August 2017.
    [pdf][long][arxiv][data][press release]
  • A Deep Learning Approach for Generalized Speech Animation
    Sarah Taylor, Taehwan Kim, Yisong Yue, Moshe Mahler, James Krahe, Anastasio Garcia Rodriguez, Jessica Hodgins, Iain Matthews
    ACM Conference on Computer Graphics (SIGGRAPH), July 2017.
    [pdf][long][demo video]
  • Factorized Variational Autoencoders for Modeling Audience Reactions to Movies
    Zhiwei Deng, Rajitha Navarathna, Peter Carr, Stephan Mandt, Yisong Yue, Iain Matthews, Greg Mori
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July, 2017.
    [pdf][press release][radio interview]
  • Generating Long-term Trajectories Using Deep Hierarchical Networks
    Stephan Zheng, Yisong Yue, Patrick Lucey
    Neural Information Processing Systems (NIPS), December 2016.
  • Smooth Imitation Learning for Online Sequence Prediction
    Hoang M. Le, Andrew Kang, Yisong Yue, Peter Carr
    International Conference on Machine Learning (ICML), June, 2016.
    [pdf][long][video][press release][Sports Illustrated][]
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[All Content © 2018 Yisong Yue]