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

Office: 303 Annenberg

Contact Information >

I am an assistant professor of Computing and Mathematical Sciences 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. I am also on the Scientific Committee for Caltech's new Center for Autonomous Systems and Technology (CAST).
NeurIPS Workshop
Please consider submitting to or attending the NeurIPS 2019 Workshop on Safety and Robustness in Decision-making!
PhD Recruiting
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).

I am particularly interested in pushing machine learning technologies toward increasingly sophisticated real-world use cases. My foundational research is centered around developing novel methods for interactive machine learning and structured machine learning. 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, experiment design for science, protein engineering, program synthesis, learning-accelerated optimization, robotics, and adaptive planning & allocation problems.
Selected Recent Publications & Preprints:
  • Preference-Based Learning for Exoskeleton Gait Optimization
    Maegan Tucker, Ellen Novoseller, Claudia Kann, Yanan Sui, Yisong Yue, Joel Burdick, Aaron D. Ames
  • Learning Calibratable Policies using Programmatic Style-Consistency
    Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht
  • Imitation-Projected Programmatic Reinforcement Learning
    Abhinav Verma, Hoang M. Le, Yisong Yue, Swarat Chaudhuri
    Neural Information Processing Systems (NeurIPS), December 2019.
  • Co-Training for Policy Learning
    Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono
    Conference on Uncertainty in Artificial Intelligence (UAI), July 2019.
    (Oral Presentation)
  • Batch Policy Learning under Constraints
    Hoang M. Le, Cameron Voloshin, Yisong Yue
    International Conference on Machine Learning (ICML), June 2019.
    (Oral Presentation)
  • Neural Lander: Stable Drone Landing Control using Learned Dynamics
    Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung
    International Conference on Robotics and Automation (ICRA), May 2019.
    [pdf][arxiv][demo video][press release]
  • A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes
    Jialin Song, Yuxin Chen, Yisong Yue
    International Conference on Artificial Intelligence and Statistics (AISTATS), April 2019.
  • Hierarchical Imitation and Reinforcement Learning
    Hoang M. Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III
    International Conference on Machine Learning (ICML), July 2018.
  • Iterative Amortized Inference
    Joseph Marino, Yisong Yue, Stephan Mandt
    International Conference on Machine Learning (ICML), July 2018.
  • Multi-dueling Bandits with Dependent Arms
    Yanan Sui, Vincent Zhuang, Joel Burdick, Yisong Yue
    Conference on Uncertainty in Artificial Intelligence (UAI), August 2017.
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[All Content © 2019 Yisong Yue]