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Fang-Yi Yu
Person information
- affiliation: George Mason University, Fairfax, VA, USA
- affiliation (PhD 2019): University of Michigan, Ann Arbor, MI, USA
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2020 – today
- 2024
- [i15]Yongkang Guo, Jason D. Hartline, Zhihuan Huang, Yuqing Kong, Anant Shah, Fang-Yi Yu:
Algorithmic Robust Forecast Aggregation. CoRR abs/2401.17743 (2024) - 2023
- [c24]Prathamesh Dharangutte, Jie Gao, Ruobin Gong, Fang-Yi Yu:
Integer Subspace Differential Privacy. AAAI 2023: 7349-7357 - [c23]M. Amin Rahimian, Fang-Yi Yu, Carlos Hurtado:
Differentially Private Network Data Collection for Influence Maximization. AAMAS 2023: 2795-2797 - [c22]Georgios Piliouras
, Fang-Yi Yu:
Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos. EC 2023: 1047-1074 - [i14]Yichi Zhang, Fang-Yi Yu, Grant Schoenebeck, David Kempe:
A System-Level Analysis of Conference Peer Review. CoRR abs/2303.09020 (2023) - [i13]M. Amin Rahimian
, Fang-Yi Yu, Carlos Hurtado:
Seeding with Differentially Private Network Information. CoRR abs/2305.16590 (2023) - 2022
- [j2]Grant Schoenebeck
, Biaoshuai Tao, Fang-Yi Yu:
Think globally, act locally: On the optimal seeding for nonsubmodular influence maximization. Inf. Comput. 285(Part): 104919 (2022) - [j1]Grant Schoenebeck
, Fang-Yi Yu
:
Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question. ACM Trans. Economics and Comput. 10(4): 14:1-14:26 (2022) - [c21]Jie Gao, Ruobin Gong, Fang-Yi Yu:
Subspace Differential Privacy. AAAI 2022: 3986-3995 - [c20]Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu:
Optimal Local Bayesian Differential Privacy over Markov Chains. AAMAS 2022: 1563-1565 - [c19]Shi Feng, Fang-Yi Yu, Yiling Chen:
Peer Prediction for Learning Agents. NeurIPS 2022 - [c18]Yichi Zhang
, Fang-Yi Yu, Grant Schoenebeck
, David Kempe:
A System-Level Analysis of Conference Peer Review. EC 2022: 1041-1080 - [i12]Georgios Piliouras, Fang-Yi Yu:
Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos. CoRR abs/2201.10483 (2022) - [i11]Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu:
Optimal Local Bayesian Differential Privacy over Markov Chains. CoRR abs/2206.11402 (2022) - [i10]Shi Feng, Fang-Yi Yu, Yiling Chen:
Peer Prediction for Learning Agents. CoRR abs/2208.04433 (2022) - [i9]Prathamesh Dharangutte, Jie Gao, Ruobin Gong, Fang-Yi Yu:
Integer Subspace Differential Privacy. CoRR abs/2212.00936 (2022) - 2021
- [c17]Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu:
Timely Information from Prediction Markets. AAMAS 2021: 1145-1153 - [c16]Yiling Chen, Biaoshuai Tao, Fang-Yi Yu:
Cooperation in Threshold Public Projects with Binary Actions. IJCAI 2021: 104-110 - [c15]Grant Schoenebeck
, Fang-Yi Yu
:
Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach. ITCS 2021: 78:1-78:20 - [c14]Shuran Zheng, Fang-Yi Yu, Yiling Chen:
The Limits of Multi-task Peer Prediction. EC 2021: 907-926 - [c13]Grant Schoenebeck
, Fang-Yi Yu, Yichi Zhang
:
Information Elicitation from Rowdy Crowds. WWW 2021: 3974-3986 - [i8]Yiling Chen, Biaoshuai Tao, Fang-Yi Yu:
Cooperation in Threshold Public Projects with Binary Actions. CoRR abs/2105.08572 (2021) - [i7]Shuran Zheng, Fang-Yi Yu, Yiling Chen:
The Limits of Multi-task Peer Prediction. CoRR abs/2106.03176 (2021) - [i6]Yiling Chen, Fang-Yi Yu:
Optimal Scoring Rule Design. CoRR abs/2107.07420 (2021) - [i5]Jie Gao, Ruobin Gong, Fang-Yi Yu:
Subspace Differential Privacy. CoRR abs/2108.11527 (2021) - 2020
- [c12]Yuqing Kong, Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
:
Information Elicitation Mechanisms for Statistical Estimation. AAAI 2020: 2095-2102 - [c11]Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
:
Limitations of Greed: Influence Maximization in Undirected Networks Re-visited. AAMAS 2020: 1224-1232 - [c10]Grant Schoenebeck
, Fang-Yi Yu
:
Escaping Saddle Points in Constant Dimensional Spaces: An Agent-based Modeling Perspective. EC 2020: 49-67 - [c9]Grant Schoenebeck
, Fang-Yi Yu
:
Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question. WINE 2020: 119-132 - [i4]Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu:
Limitations of Greed: Influence Maximization in Undirected Networks Re-visited. CoRR abs/2002.11679 (2020) - [i3]Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu:
Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization. CoRR abs/2003.10393 (2020) - [i2]Grant Schoenebeck, Fang-Yi Yu:
Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach. CoRR abs/2009.14730 (2020) - [i1]Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu:
Timely Information from Prediction Markets. CoRR abs/2011.03645 (2020)
2010 – 2019
- 2019
- [b1]Fang-Yi Yu:
Dynamics and Social Networks. University of Michigan, USA, 2019 - [c8]Grant Schoenebeck
, Biaoshuai Tao
, Fang-Yi Yu
:
Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization. APPROX-RANDOM 2019: 39:1-39:20 - [c7]Jie Gao, Grant Schoenebeck
, Fang-Yi Yu
:
The Volatility of Weak Ties: Co-evolution of Selection and Influence in Social Networks. AAMAS 2019: 619-627 - 2018
- [c6]Grant Schoenebeck
, Fang-Yi Yu
:
Consensus of Interacting Particle Systems on Erdös-Rényi Graphs. SODA 2018: 1945-1964 - 2017
- [c5]Jie Gao, Bo Li, Grant Schoenebeck, Fang-Yi Yu
:
Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents. AAAI 2017: 537-543 - [c4]Jie Gao, Grant Schoenebeck
, Fang-Yi Yu:
Cascades and Myopic Routing in Nonhomogeneous Kleinberg's Small World Model. WINE 2017: 383-394 - 2016
- [c3]Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck
, Fang-Yi Yu
:
General Threshold Model for Social Cascades: Analysis and Simulations. EC 2016: 617-634 - [c2]Grant Schoenebeck
, Aaron Snook, Fang-Yi Yu
:
Sybil Detection Using Latent Network Structure. EC 2016: 739-756 - [c1]Grant Schoenebeck
, Fang-Yi Yu:
Complex Contagions on Configuration Model Graphs with a Power-Law Degree Distribution. WINE 2016: 459-472
Coauthor Index
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last updated on 2024-05-08 21:00 CEST by the dblp team
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