Grant Schoenebeck

ORCID

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 77

Top Venues

CoRR

WINE

ITCS

Publications

Noah Burrell, Grant Schoenebeck
Testing conventional wisdom (of the crowd). UAI (2023)
Yichi Zhang, Grant Schoenebeck
Multitask Peer Prediction With Task-dependent Strategies. WWW (2023)
Qishen Han, Grant Schoenebeck, Biaoshuai Tao, Lirong Xia
The Wisdom of Strategic Voting. EC (2023)
Noah Burrell, Grant Schoenebeck
Measurement Integrity in Peer Prediction: A Peer Assessment Case Study. EC (2023)
Qishen Han, Grant Schoenebeck, Biaoshuai Tao, Lirong Xia
The Wisdom of Strategic Voting. CoRR (2023)
Yuqing Kong, Grant Schoenebeck
False Consensus, Information Theory, and Prediction Markets. ITCS (2023)
Yichi Zhang, Grant Schoenebeck, Weijie Su
Eliciting Honest Information From Authors Using Sequential Review. CoRR (2023)
Yichi Zhang, Grant Schoenebeck
High-Effort Crowds: Limited Liability via Tournaments. WWW (2023)
Yichi Zhang, Fang-Yi Yu, Grant Schoenebeck, David Kempe
A System-Level Analysis of Conference Peer Review. CoRR (2023)
Zhihuan Huang, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck, Shengwei Xu
BONUS! Maximizing Surprise. WWW (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)
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
Think globally, act locally: On the optimal seeding for nonsubmodular influence maximization. Inf. Comput. 285 (Part) (2022)
Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization. J. Artif. Intell. Res. 74 (2022)
Yichi Zhang, Fang-Yi Yu, Grant Schoenebeck, David Kempe
A System-Level Analysis of Conference Peer Review. EC (2022)
Yuqing Kong, Grant Schoenebeck
False Consensus, Information Theory, and Prediction Markets. CoRR (2022)
Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu
Optimal Local Bayesian Differential Privacy over Markov Chains. CoRR (2022)
Shih-Tang Su, Vijay G. Subramanian, Grant Schoenebeck
Bayesian Persuasion in Sequential Trials. WINE (2021)
Grant Schoenebeck, Biaoshuai Tao
Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences. CoRR (2021)
Noah Burrell, Grant Schoenebeck
Relaxing Common Belief for Social Networks. ITCS (2021)
Grant Schoenebeck, Biaoshuai Tao
Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences. NeurIPS (2021)
Noah Burrell, Grant Schoenebeck
Measurement Integrity in Peer Prediction: A Peer Assessment Case Study. CoRR (2021)
Grant Schoenebeck, Fang-Yi Yu
Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach. ITCS (2021)
Zhihuan Huang, Shengwei Xu, You Shan, Yuxuan Lu, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck
SURPRISE! and When to Schedule It. CoRR (2021)
Shih-Tang Su, Vijay G. Subramanian, Grant Schoenebeck
Bayesian Persuasion in Sequential Trials. CoRR (2021)
Grant Schoenebeck, Fang-Yi Yu, Yichi Zhang
Information Elicitation from Rowdy Crowds. WWW (2021)
Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu
Timely Information from Prediction Markets. AAMAS (2021)
Paul Resnick, Yuqing Kong, Grant Schoenebeck, Tim Weninger
Survey Equivalence: A Procedure for Measuring Classifier Accuracy Against Human Labels. CoRR (2021)
Zhihuan Huang, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck, Shengwei Xu
BONUS! Maximizing Surprise. CoRR (2021)
Zhihuan Huang, Shengwei Xu, You Shan, Yuxuan Lu, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck
SURPRISE! and When to Schedule It. IJCAI (2021)
Grant Schoenebeck, Biaoshuai Tao
Influence Maximization on Undirected Graphs: Toward Closing the (1-1/e) Gap. ACM Trans. Economics and Comput. 8 (4) (2020)
Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization. AAAI (2020)
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)
Noah Burrell, Grant Schoenebeck
Relaxing Common Belief for Social Networks. CoRR (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
Beyond Worst-case (In)approximability of Nonsubmodular Influence Maximization. ACM Trans. Comput. Theory 11 (3) (2019)
Yuqing Kong, Grant Schoenebeck
An Information Theoretic Framework For Designing Information Elicitation Mechanisms That Reward Truth-telling. ACM Trans. Economics and Comput. 7 (1) (2019)
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization. APPROX-RANDOM (2019)
Grant Schoenebeck, Biaoshuai Tao
Influence Maximization on Undirected Graphs: Towards Closing the (1-1/e) Gap. EC (2019)
Yuqing Kong, Chris Peikert, Grant Schoenebeck, Biaoshuai Tao
Outsourcing Computation: The Minimal Refereed Mechanism. WINE (2019)
Jie Gao, Grant Schoenebeck, Fang-Yi Yu
The Volatility of Weak Ties: Co-evolution of Selection and Influence in Social Networks. AAMAS (2019)
Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization. CoRR (2019)
Shih-Tang Su, Vijay G. Subramanian, Grant Schoenebeck
Social learning with questions. NetEcon@SIGMETRICS (2019)
Yuqing Kong, Chris Peikert, Grant Schoenebeck, Biaoshuai Tao
Outsourcing Computation: the Minimal Refereed Mechanism. CoRR (2019)
Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi N. R. Wijewickrema, Michael E. Houle, Grant Schoenebeck, Dawn Song, James Bailey
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. CoRR (2018)
Yuqing Kong, Grant Schoenebeck
Optimizing Bayesian Information Revelation Strategy in Prediction Markets: the Alice Bob Alice Case. ITCS (2018)
Yuqing Kong, Grant Schoenebeck
Eliciting Expertise without Verification. CoRR (2018)
Grant Schoenebeck, Fang-Yi Yu
Consensus of Interacting Particle Systems on Erdös-Rényi Graphs. SODA (2018)
Yuqing Kong, Grant Schoenebeck
Eliciting Expertise without Verification. EC (2018)
Boyu Tian, Jiamin Huang, Barzan Mozafari, Grant Schoenebeck
Contention-Aware Lock Scheduling for Transactional Databases. Proc. VLDB Endow. 11 (5) (2018)
Yuqing Kong, Grant Schoenebeck
Water from Two Rocks: Maximizing the Mutual Information. CoRR (2018)
Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi N. R. Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E. Houle, James Bailey
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. ICLR (2018)
Grant Schoenebeck, Shih-Tang Su, Vijay G. Subramanian
Social Learning with Questions. CoRR (2018)
Yuqing Kong, Grant Schoenebeck
Equilibrium Selection in Information Elicitation without Verification via Information Monotonicity. ITCS (2018)
Yuqing Kong, Grant Schoenebeck
Water from Two Rocks: Maximizing the Mutual Information. EC (2018)
Grant Schoenebeck, Biaoshuai Tao
Beyond Worst-Case (In)approximability of Nonsubmodular Influence Maximization. WINE (2017)
Jie Gao, Bo Li, Grant Schoenebeck, Fang-Yi Yu
Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents. AAAI (2017)
Grant Schoenebeck, Biaoshuai Tao
Beyond Worst-Case (In)approximability of Nonsubmodular Influence Maximization. CoRR (2017)
Rico Angell, Grant Schoenebeck
Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization. WINE (2017)
Jiamin Huang, Barzan Mozafari, Grant Schoenebeck, Thomas F. Wenisch
A Top-Down Approach to Achieving Performance Predictability in Database Systems. SIGMOD Conference (2017)
Jie Gao, Grant Schoenebeck, Fang-Yi Yu
Cascades and Myopic Routing in Nonhomogeneous Kleinberg's Small World Model. WINE (2017)
Roozbeh Ebrahimi, Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck
How Complex Contagions Spread Quickly in Preferential Attachment Models and Other Time-Evolving Networks. IEEE Trans. Netw. Sci. Eng. 4 (4) (2017)
Yuqing Kong, Grant Schoenebeck
A Framework For Designing Information Elicitation Mechanisms That Reward Truth-telling. CoRR (2016)
Rico Angell, Grant Schoenebeck
Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization. CoRR (2016)
Yuqing Kong, Katrina Ligett, Grant Schoenebeck
Putting Peer Prediction Under the Micro(economic)scope and Making Truth-Telling Focal. WINE (2016)
Yuqing Kong, Grant Schoenebeck
Equilibrium Selection in Information Elicitation without Verification via Information Monotonicity. CoRR (2016)
Grant Schoenebeck, Aaron Snook, Fang-Yi Yu
Sybil Detection Using Latent Network Structure. EC (2016)
Yuqing Kong, Grant Schoenebeck, Katrina Ligett
Putting Peer Prediction Under the Micro(economic)scope and Making Truth-telling Focal. CoRR (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)
Roozbeh Ebrahimi, Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck
Complex Contagions in Kleinberg's Small World Model. ITCS (2015)
Travis Martin, Grant Schoenebeck, Michael P. Wellman
Characterizing strategic cascades on networks. EC (2014)
Arpita Ghosh, Katrina Ligett, Aaron Roth, Grant Schoenebeck
Buying private data without verification. EC (2014)
Roozbeh Ebrahimi, Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck
How Complex Contagions Spread and Spread Quickly. CoRR (2014)
Roozbeh Ebrahimi, Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck
Complex Contagions in Kleinberg's Small World Model. CoRR (2014)
Arpita Ghosh, Katrina Ligett, Aaron Roth, Grant Schoenebeck
Buying Private Data without Verification. CoRR (2014)
Aaron Snook, Grant Schoenebeck, Paolo Codenotti
Graph Isomorphism and the Lasserre Hierarchy. CoRR (2014)
Shiri Chechik, Daniel H. Larkin, Liam Roditty, Grant Schoenebeck, Robert Endre Tarjan, Virginia Vassilevska Williams
Better Approximation Algorithms for the Graph Diameter. SODA (2014)
Grant Schoenebeck
Potential networks, contagious communities, and understanding social network structure. WWW (2013)
Grant Schoenebeck
Potential Networks, Contagious Communities, and Understanding Social Network Structure CoRR (2013)
Travis Martin, Grant Schoenebeck, Michael P. Wellman
Characterizing Strategic Cascades on Networks. CoRR (2013)
Aaron Roth, Grant Schoenebeck
Conducting Truthful Surveys, Cheaply CoRR (2012)
Sanjeev Arora, Rong Ge, Sushant Sachdeva, Grant Schoenebeck
Finding overlapping communities in social networks: toward a rigorous approach. EC (2012)
Grant Schoenebeck, Salil P. Vadhan
The Computational Complexity of Nash Equilibria in Concisely Represented Games. ACM Trans. Comput. Theory 4 (2) (2012)
Aaron Roth, Grant Schoenebeck
Conducting truthful surveys, cheaply. EC (2012)
Rafael M. Frongillo, Grant Schoenebeck, Omer Tamuz
Social Learning in a Changing World CoRR (2011)
Sanjeev Arora, Rong Ge, Sushant Sachdeva, Grant Schoenebeck
Finding Overlapping Communities in Social Networks: Toward a Rigorous Approach CoRR (2011)
Rafael M. Frongillo, Grant Schoenebeck, Omer Tamuz
Social Learning in a Changing World. WINE (2011)
Thomas Holenstein, Grant Schoenebeck
General Hardness Amplification of Predicates and Puzzles - (Extended Abstract). TCC (2011)
Anupam Gupta, Aaron Roth, Grant Schoenebeck, Kunal Talwar
Constrained Non-Monotone Submodular Maximization: Offline and Secretary Algorithms CoRR (2010)
Sarita Yardi, Daniel M. Romero, Grant Schoenebeck, danah boyd
Detecting Spam in a Twitter Network. First Monday 15 (1) (2010)
Elchanan Mossel, Grant Schoenebeck
Reaching Consensus on Social Networks. ICS (2010)
Arnab Bhattacharyya, Swastik Kopparty, Grant Schoenebeck, Madhu Sudan, David Zuckerman
Optimal Testing of Reed-Muller Codes. FOCS (2010)
Anupam Gupta, Aaron Roth, Grant Schoenebeck, Kunal Talwar
Constrained Non-monotone Submodular Maximization: Offline and Secretary Algorithms. WINE (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Grant Schoenebeck