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

Office: 303 Annenberg

Contact Information >

I am a 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).
ICML Workshop
Please consider participating in our (virtual) workshop on Real World Experiment Design and Active Learning, hosted by ICML 2020.
My research interests lie primarily in machine learning, and spans the entire theory-to-application spectrum from foundational advances all the way to deployment in real systems. My core interest is in developing practical theory of machine learning that pushes principled algorithm design towards real-world applications. I work closely with domain experts to understand the frontier challenges in applied machine learning, distill those challenges into mathematically precise formulations, and develop novel methods to tackle them.

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:
  • Beyond No-Regret: Competitive Control via Online Optimization with Memory
    Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman
  • On the distance between two neural networks and the stability of learning
    Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu
  • Learning Calibratable Policies using Programmatic Style-Consistency
    Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht
  • Preference-Based Learning for Exoskeleton Gait Optimization
    Maegan Tucker, Ellen Novoseller, Claudia Kann, Yanan Sui, Yisong Yue, Joel Burdick, Aaron D. Ames
    International Conference on Robotics and Automation (ICRA), May 2020.
    (Best Paper Nomination)
    [pdf][arxiv][demo video][project]
  • Imitation-Projected Programmatic Reinforcement Learning
    Abhinav Verma, Hoang M. Le, Yisong Yue, Swarat Chaudhuri
    Neural Information Processing Systems (NeurIPS), December 2019.
    [pdf][arxiv][code][demo video]
  • 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]
  • 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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