General Threshold Model for Social Cascades: Analysis and Simulations. - Jie Gao 001; Golnaz Ghasemiesfeh; Grant Schoenebeck; Fang-Yi Yu (EC, 2016)

Sybil Detection Using Latent Network Structure. - Grant Schoenebeck; Aaron Snook; Fang-Yi Yu (EC, 2016)

Complex Contagions on Configuration Model Graphs with a Power-Law Degree Distribution. - Grant Schoenebeck; Fang-Yi Yu (WINE, 2016)

Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents. - Jie Gao 001; Bo Li 026; Grant Schoenebeck; Fang-Yi Yu (AAAI, 2017)

Cascades and Myopic Routing in Nonhomogeneous Kleinberg's Small World Model. - Jie Gao 001; Grant Schoenebeck; Fang-Yi Yu (WINE, 2017)

Consensus of Interacting Particle Systems on Erdös-Rényi Graphs. - Grant Schoenebeck; Fang-Yi Yu (SODA, 2018)

The Volatility of Weak Ties: Co-evolution of Selection and Influence in Social Networks. - Jie Gao 001; Grant Schoenebeck; Fang-Yi Yu (AAMAS, 2019)

Dynamics and Social Networks. - Fang-Yi Yu (2019)

Information Elicitation Mechanisms for Statistical Estimation. - Yuqing Kong; Grant Schoenebeck; Biaoshuai Tao; Fang-Yi Yu (AAAI, 2020)

Limitations of Greed: Influence Maximization in Undirected Networks Re-visited. - Grant Schoenebeck; Biaoshuai Tao; Fang-Yi Yu (AAMAS, 2020)

Escaping Saddle Points in Constant Dimensional Spaces: An Agent-based Modeling Perspective. - Grant Schoenebeck; Fang-Yi Yu (EC, 2020)

Timely Information from Prediction Markets. - Grant Schoenebeck; Chenkai Yu; Fang-Yi Yu (AAMAS, 2021)

Cooperation in Threshold Public Projects with Binary Actions. - Yiling Chen 001; Biaoshuai Tao; Fang-Yi Yu (IJCAI, 2021)

Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach. - Grant Schoenebeck; Fang-Yi Yu (ITCS, 2021)

The Limits of Multi-task Peer Prediction. - Shuran Zheng; Fang-Yi Yu; Yiling Chen 001 (EC, 2021)

Information Elicitation from Rowdy Crowds. - Grant Schoenebeck; Fang-Yi Yu; Yichi Zhang 003 (WWW, 2021)

Optimal Scoring Rule Design. - Yiling Chen 001; Fang-Yi Yu (CoRR, 2021)

Subspace Differential Privacy. - Jie Gao 001; Ruobin Gong; Fang-Yi Yu (AAAI, 2022)

Optimal Local Bayesian Differential Privacy over Markov Chains. - Darshan Chakrabarti; Jie Gao 001; Aditya Saraf; Grant Schoenebeck; Fang-Yi Yu (AAMAS, 2022)

Peer Prediction for Learning Agents. - Shi Feng 002; Fang-Yi Yu; Yiling Chen 001 (NeurIPS, 2022)

A System-Level Analysis of Conference Peer Review. - Yichi Zhang 003; Fang-Yi Yu; Grant Schoenebeck; David Kempe 001 (EC, 2022)

Think globally, act locally: On the optimal seeding for nonsubmodular influence maximization. - Grant Schoenebeck; Biaoshuai Tao; Fang-Yi Yu (Inf. Comput., 2022)

Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question. - Grant Schoenebeck; Fang-Yi Yu (ACM Trans. Economics and Comput., 2022)

Integer Subspace Differential Privacy. - Prathamesh Dharangutte; Jie Gao 001; Ruobin Gong; Fang-Yi Yu (AAAI, 2023)

Differentially Private Network Data Collection for Influence Maximization. - M. Amin Rahimian; Fang-Yi Yu; Carlos Hurtado (AAMAS, 2023)

Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos. - Georgios Piliouras; Fang-Yi Yu (EC, 2023)

Seeding with Differentially Private Network Information. - M. Amin Rahimian; Fang-Yi Yu; Carlos Hurtado (CoRR, 2023)

Carrot and Stick: Eliciting Comparison Data and Beyond. - Yiling Chen; Shi Feng; Fang-Yi Yu (NeurIPS, 2024)

Hardness and Approximation Algorithms for Balanced Districting Problems. - Prathamesh Dharangutte; Jie Gao 001; Shang-En Huang; Fang-Yi Yu (FORC, 2025)

Algorithmic Robust Forecast Aggregation. - Yongkang Guo; Jason D. Hartline; Zhihuan Huang; Yuqing Kong; Anant Shah; Fang-Yi Yu (EC, 2025)

Designing Automated Market Makers for Combinatorial Securities: A Geometric Viewpoint. - Prommy Sultana Hossain; Xintong Wang; Fang-Yi Yu (SODA, 2025)