Fang-Yi Yu

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 41

Top Topics

Differentially Private

Differential Privacy

Influence Maximization

Top Venues

Publications

Yongkang Guo, Jason D. Hartline, Zhihuan Huang, Yuqing Kong, Anant Shah, Fang-Yi Yu
Algorithmic Robust Forecast Aggregation. CoRR (2024)
M. Amin Rahimian, Fang-Yi Yu, Carlos Hurtado
Seeding with Differentially Private Network Information. CoRR (2023)
Prathamesh Dharangutte, Jie Gao, Ruobin Gong, Fang-Yi Yu
Integer Subspace Differential Privacy. AAAI (2023)
Yichi Zhang, Fang-Yi Yu, Grant Schoenebeck, David Kempe
A System-Level Analysis of Conference Peer Review. CoRR (2023)
Georgios Piliouras, Fang-Yi Yu
Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos. EC (2023)
M. Amin Rahimian, Fang-Yi Yu, Carlos Hurtado
Differentially Private Network Data Collection for Influence Maximization. AAMAS (2023)
Shi Feng, Fang-Yi Yu, Yiling Chen
Peer Prediction for Learning Agents. NeurIPS (2022)
Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu
Optimal Local Bayesian Differential Privacy over Markov Chains. AAMAS (2022)
Grant Schoenebeck, Fang-Yi Yu
Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question. ACM Trans. Economics and Comput. 10 (4) (2022)
Prathamesh Dharangutte, Jie Gao, Ruobin Gong, Fang-Yi Yu
Integer Subspace Differential Privacy. CoRR (2022)
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
Think globally, act locally: On the optimal seeding for nonsubmodular influence maximization. Inf. Comput. 285 (Part) (2022)
Shi Feng, Fang-Yi Yu, Yiling Chen
Peer Prediction for Learning Agents. CoRR (2022)
Georgios Piliouras, Fang-Yi Yu
Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos. CoRR (2022)
Jie Gao, Ruobin Gong, Fang-Yi Yu
Subspace Differential Privacy. AAAI (2022)
Yichi Zhang, Fang-Yi Yu, Grant Schoenebeck, David Kempe
A System-Level Analysis of Conference Peer Review. EC (2022)
Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu
Optimal Local Bayesian Differential Privacy over Markov Chains. CoRR (2022)
Shuran Zheng, Fang-Yi Yu, Yiling Chen
The Limits of Multi-task Peer Prediction. EC (2021)
Shuran Zheng, Fang-Yi Yu, Yiling Chen
The Limits of Multi-task Peer Prediction. CoRR (2021)
Yiling Chen, Biaoshuai Tao, Fang-Yi Yu
Cooperation in Threshold Public Projects with Binary Actions. CoRR (2021)
Grant Schoenebeck, Fang-Yi Yu
Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach. ITCS (2021)
Grant Schoenebeck, Fang-Yi Yu, Yichi Zhang
Information Elicitation from Rowdy Crowds. WWW (2021)
Yiling Chen, Biaoshuai Tao, Fang-Yi Yu
Cooperation in Threshold Public Projects with Binary Actions. IJCAI (2021)
Yiling Chen, Fang-Yi Yu
Optimal Scoring Rule Design. CoRR (2021)
Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu
Timely Information from Prediction Markets. AAMAS (2021)
Jie Gao, Ruobin Gong, Fang-Yi Yu
Subspace Differential Privacy. CoRR (2021)
Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu
Timely Information from Prediction Markets. CoRR (2020)
Grant Schoenebeck, Fang-Yi Yu
Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question. WINE (2020)
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
Limitations of Greed: Influence Maximization in Undirected Networks Re-visited. CoRR (2020)
Yuqing Kong, Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
Information Elicitation Mechanisms for Statistical Estimation. AAAI (2020)
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization. CoRR (2020)
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
Limitations of Greed: Influence Maximization in Undirected Networks Re-visited. AAMAS (2020)
Grant Schoenebeck, Fang-Yi Yu
Escaping Saddle Points in Constant Dimensional Spaces: An Agent-based Modeling Perspective. EC (2020)
Grant Schoenebeck, Fang-Yi Yu
Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach. CoRR (2020)
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization. APPROX-RANDOM (2019)
Jie Gao, Grant Schoenebeck, Fang-Yi Yu
The Volatility of Weak Ties: Co-evolution of Selection and Influence in Social Networks. AAMAS (2019)
Grant Schoenebeck, Fang-Yi Yu
Consensus of Interacting Particle Systems on Erdös-Rényi Graphs. SODA (2018)
Jie Gao, Bo Li, Grant Schoenebeck, Fang-Yi Yu
Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents. AAAI (2017)
Jie Gao, Grant Schoenebeck, Fang-Yi Yu
Cascades and Myopic Routing in Nonhomogeneous Kleinberg's Small World Model. WINE (2017)
Grant Schoenebeck, Aaron Snook, Fang-Yi Yu
Sybil Detection Using Latent Network Structure. EC (2016)
Grant Schoenebeck, Fang-Yi Yu
Complex Contagions on Configuration Model Graphs with a Power-Law Degree Distribution. WINE (2016)
Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck, Fang-Yi Yu
General Threshold Model for Social Cascades: Analysis and Simulations. EC (2016)