Fang-Yi Yu

I am a postdoctoral fellow at Harvard John A. Paulson School of Engineering and Applied Sciences hosted by Yiling Chen.

I received my Ph.D. degree in ​ Computer Science and Engineering Division from the University of Michigan advised by Grant Schoenebeck.

I am on the academic job market. Please reach out to me if you are hiring!

Research Interests

Machine Learning with strategic agents, economics and computation, and theoretical computer science

Maniscript

  1. Optimal Scoring Rule Design
    Yiling Chen, Fang-Yi Yu.

Peer-reviewed papers

  1. Optimal Local Bayesian Differential Privacy over Markov Chains
    Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu.
    The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022).

  2. Subspace Differential Privacy
    Jie Gao, Ruobin Gong, Fang-Yi Yu.
    The 36th International Conference on Artificial Intelligence (AAAI 2022).

  3. The Limits of Multi-task Peer Prediction
    Shuran Zheng, Fang-Yi Yu, Yiling Chen.
    The 22th ACM Conference on Economics and Computation (EC 2021).

  4. ​Cooperation in Threshold Public Projects with Binary Actions
    Yiling Chen, Biaoshuai Tao, Fang-Yi Yu.
    The 30th International Joint Conference on Artificial Intelligence (IJCAI 2021).

  5. Information Elicitation from Rowdy Crowds
    Grant Schoenebeck, Fang-Yi Yu, Yichi Zhang.
    The 30th Web Conference (WWW 2021).

  6. Timely Information from Prediction Markets
    Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu.
    The 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021).

  7. Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach
    Grant Schoenebeck, Fang-Yi Yu.
    The 12th Innovations in Theoretical Computer Science Conference (ITCS 2021). [poster]

  8. Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question
    Grant Schoenebeck, Fang-Yi Yu.
    The 16th International Conference on Web and Internet Economics (WINE 2020). [slides, poster, video]

  9. Escaping Saddle Points in Constant Dimensional Spaces: an Agent-based Modeling Perspective
    Grant Schoenebeck, Fang-Yi Yu.
    The 21st ACM Conference on Economics and Computation (EC 2020). [slides, short slides, poster, video]

  10. Limitations of Greed: Influence Maximization in Undirected Networks Re-visited
    Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu.
    The 19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2020).

  11. Information Elicitation Mechanisms for Statistical Estimation
    Yuqing Kong, Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu.
    The 34th International Conference on Artificial Intelligence (AAAI 2020). [poster]

  12. Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization​​​
    Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu.
    The 23th International Conference on Randomization and Computation (RANDOM 2019). [slides]

  13. The Volatility of Weak Ties: Co-evolution of Selection and Influence in Social Networks
    Jie Gao, Grant Schoenebeck, Fang-Yi Yu.
    The 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019). [slides]

  14. Consensus of Interacting Particle Systems on Erdös-Rényi Graphs
    Grant Schoenebeck, Fang-Yi Yu.
    The 29th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2018). [slides]

  15. Cascades and Myopic Routing in Nonhomogeneous Kleinberg’s Small World Model
    Jie Gao, Grant Schoenebeck, Fang-Yi Yu.
    The 13th International Conference on Web and Internet Economics (WINE 2017). [slides]

  16. Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents
    Jie Gao, Bo Li, Grant Schoenebeck, Fang-Yi Yu.
    The 30th International Conference on Artificial Intelligence (AAAI 2017). [slides]

  17. Complex Contagions on Configuration Model Graphs with a Power-Law Degree Distribution
    Grant Schoenebeck, Fang-Yi Yu.
    The 12th Conference on Web and Internet Economics (WINE 2016). [slides]

  18. Sybil Detection Using Latent Network Structure
    Aaron Snook, Grant Schoenebeck, Fang-Yi Yu.
    The 17th ACM Conference on Economics and Computation (EC 2016). [slides]

  19. General Threshold Model for Social Cascades: Analysis and Simulations
    Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck, Fang-Yi Yu.
    The 17th ACM Conference on Economics and Computation (EC 2016). [slides]