Yisong Yue (he/him)
California Institute of Technology
1200 E. California Blvd.
CMS, 305-16
Pasadena, CA 91125

Office: 303 Annenberg

Contact Information >

About
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).
Diversity, Equity & Inclusion
I am committed to promoting diversity, equity, and inclusion in my research group, in my courses, within the CMS department, at Caltech more broadly, and within my research communities.
  • Diversity -- I recognize that diversity, in all its shapes and forms, strengthens us both culturally and intellectually.
  • Equity -- I will fight for equal treatment of all people, regardless of race, gender, sexual orientation, or any other attributes that are completely irrelevant to academic and research potential.
  • Inclusion -- I will work to create an inclusive working environment, so that everyone feels their voices are heard and their contributions are recognized.
Faculty Openings
We have multiple faculty openings, and are searching in all areas of computing and mathematical sciences. More information is available here.
NeurIPS Workshop
Please consider participating in our Workshop on Learning Meets Combinatorial Algorithms, hosted by NeurIPS 2020.
Research
My research interests lie primarily in machine learning, and span 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:
  • Iterative Amortized Policy Optimization
    Joseph Marino, Alexandre Piché, Alessandro Davide Ialongo, Yisong Yue
    [arxiv][code]
  • A General Large Neighborhood Search Framework for Solving Integer Programs
    Jialin Song, Ravi Lanka, Yisong Yue, Bistra Dilkina
    Neural Information Processing Systems (NeurIPS), December 2020.
    [pdf][arxiv][code]
  • Online Optimization with Memory and Competitive Control
    Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman
    Neural Information Processing Systems (NeurIPS), December 2020.
    [arxiv]
  • On the distance between two neural networks and the stability of learning
    Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu
    Neural Information Processing Systems (NeurIPS), December 2020.
    [arxiv][code]
  • Learning Calibratable Policies using Programmatic Style-Consistency
    Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht
    International Conference on Machine Learning (ICML), July 2020.
    [pdf][arxiv][code][demo]
  • 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 Award)
    [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]
  • Batch Policy Learning under Constraints
    Hoang M. Le, Cameron Voloshin, Yisong Yue
    International Conference on Machine Learning (ICML), June 2019.
    (Oral Presentation)
    [pdf][arxiv][project]
  • 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]
  • Multi-dueling Bandits with Dependent Arms
    Yanan Sui, Vincent Zhuang, Joel Burdick, Yisong Yue
    Conference on Uncertainty in Artificial Intelligence (UAI), August 2017.
    [pdf][arxiv]
News & Announcements
[All Content © 2020 Yisong Yue]