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

Office: 303 Annenberg

Contact Information >

About & Research
I am a professor of Computing and Mathematical Sciences at the California Institute of Technology. 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. 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.
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 do not define a person's 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.
Read more about diversity, equity, and inclusion at the CMS Department and EAS Division at Caltech.
Selected Recent Papers
  • Learning to Control an Unstable System with One Minute of Data: Leveraging Gaussian Process Differentiation in Predictive Control
    Ivan D. Jimenez Rodriguez, Ugo Rosolia, Aaron D. Ames, Yisong Yue
    International Conference on Intelligent Robots and Systems (IROS), September 2021.
    [arxiv]
  • Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions
    Guanya Shi, Wolfgang Hönig, Xichen Shi, Yisong Yue, Soon-Jo Chung
    IEEE Transactions on Robotics (T-RO), 2021.
    [arxiv][video][press release]
  • Task Programming: Learning Data Efficient Behavior Representations
    Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Yue, Pietro Perona
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2021.
    (Best Student Paper Award)
    [arxiv][code][project]
  • Learning to Make Decisions via Submodular Regularization
    Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen
    International Conference on Learning Representations (ICLR), May 2021.
    [pdf][poster]
  • Online Robust Control of Nonlinear Systems with Large Uncertainty
    Dimitar Ho, Hoang M. Le, John Doyle, Yisong Yue
    International Conference on Artificial Intelligence and Statistics (AISTATS), April 2021.
    [pdf][arxiv]
  • Learning Differentiable Programs with Admissible Neural Heuristics
    Ameesh Shah*, Eric Zhan*, Jennifer J. Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri
    Neural Information Processing Systems (NeurIPS), December 2020.
    [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]
  • 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]
  • 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]
  • 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]
  • Iterative Amortized Inference
    Joseph Marino, Yisong Yue, Stephan Mandt
    International Conference on Machine Learning (ICML), July 2018.
    [pdf][arxiv][code]
  • 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 © 2021 Yisong Yue]