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Grant Schoenebeck
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- affiliation: University of Michigan, USA
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2020 – today
- 2024
- [c65]Yichi Zhang, Grant Schoenebeck, Weijie Su:
Eliciting Honest Information from Authors Using Sequential Review. AAAI 2024: 9977-9984 - [c64]Yuxuan Lu, Shengwei Xu, Yichi Zhang, Yuqing Kong, Grant Schoenebeck:
Eliciting Informative Text Evaluations with Large Language Models. EC 2024: 582-612 - [c63]Md Sanzeed Anwar, Grant Schoenebeck, Paramveer S. Dhillon:
Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns. WWW 2024: 123-134 - [c62]David Gamba, Yulin Yu, Yuan Yuan, Grant Schoenebeck, Daniel M. Romero:
Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee Departures. WWW 2024: 211-222 - [c61]Shengwei Xu, Yichi Zhang, Paul Resnick, Grant Schoenebeck:
Spot Check Equivalence: An Interpretable Metric for Information Elicitation Mechanisms. WWW 2024: 276-287 - [i50]Shengwei Xu, Yichi Zhang, Paul Resnick, Grant Schoenebeck:
Spot Check Equivalence: an Interpretable Metric for Information Elicitation Mechanisms. CoRR abs/2402.13567 (2024) - [i49]Md Sanzeed Anwar, Grant Schoenebeck, Paramveer S. Dhillon:
Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns. CoRR abs/2402.15013 (2024) - [i48]David Gamba, Yulin Yu, Yuan Yuan, Grant Schoenebeck, Daniel M. Romero:
Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee Departures. CoRR abs/2402.15683 (2024) - [i47]Yuxuan Lu, Shengwei Xu, Yichi Zhang, Yuqing Kong, Grant Schoenebeck:
Eliciting Informative Text Evaluations with Large Language Models. CoRR abs/2405.15077 (2024) - [i46]Shengwei Xu, Yuxuan Lu, Grant Schoenebeck, Yuqing Kong:
Benchmarking LLMs' Judgments with No Gold Standard. CoRR abs/2411.07127 (2024) - [i45]Md Sanzeed Anwar, Paramveer S. Dhillon, Grant Schoenebeck:
Recommendation and Temptation. CoRR abs/2412.10595 (2024) - 2023
- [c60]Yuqing Kong, Grant Schoenebeck:
False Consensus, Information Theory, and Prediction Markets. ITCS 2023: 81:1-81:23 - [c59]Noah Burrell, Grant Schoenebeck:
Measurement Integrity in Peer Prediction: A Peer Assessment Case Study. EC 2023: 369-389 - [c58]Qishen Han, Grant Schoenebeck, Biaoshuai Tao, Lirong Xia:
The Wisdom of Strategic Voting. EC 2023: 885-905 - [c57]Noah Burrell, Grant Schoenebeck:
Testing conventional wisdom (of the crowd). UAI 2023: 237-248 - [c56]Yichi Zhang, Grant Schoenebeck:
Multitask Peer Prediction With Task-dependent Strategies. WWW 2023: 3436-3446 - [c55]Yichi Zhang, Grant Schoenebeck:
High-Effort Crowds: Limited Liability via Tournaments. WWW 2023: 3467-3477 - [i44]Yichi Zhang, Fang-Yi Yu, Grant Schoenebeck, David Kempe:
A System-Level Analysis of Conference Peer Review. CoRR abs/2303.09020 (2023) - [i43]Qishen Han, Grant Schoenebeck, Biaoshuai Tao, Lirong Xia:
The Wisdom of Strategic Voting. CoRR abs/2305.11021 (2023) - [i42]Yichi Zhang, Grant Schoenebeck, Weijie Su:
Eliciting Honest Information From Authors Using Sequential Review. CoRR abs/2311.14619 (2023) - 2022
- [j10]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) - [j9]Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao:
Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization. J. Artif. Intell. Res. 74: 303-351 (2022) - [j8]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) - [c54]Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu:
Optimal Local Bayesian Differential Privacy over Markov Chains. AAMAS 2022: 1563-1565 - [c53]Yichi Zhang, Fang-Yi Yu, Grant Schoenebeck, David Kempe:
A System-Level Analysis of Conference Peer Review. EC 2022: 1041-1080 - [c52]Zhihuan Huang, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck, Shengwei Xu:
BONUS! Maximizing Surprise. WWW 2022: 36-46 - [i41]Yuqing Kong, Grant Schoenebeck:
False Consensus, Information Theory, and Prediction Markets. CoRR abs/2206.02993 (2022) - [i40]Darshan Chakrabarti, Jie Gao, Aditya Saraf, Grant Schoenebeck, Fang-Yi Yu:
Optimal Local Bayesian Differential Privacy over Markov Chains. CoRR abs/2206.11402 (2022) - 2021
- [c51]Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu:
Timely Information from Prediction Markets. AAMAS 2021: 1145-1153 - [c50]Zhihuan Huang, Shengwei Xu, You Shan, Yuxuan Lu, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck:
SURPRISE! and When to Schedule It. IJCAI 2021: 252-260 - [c49]Noah Burrell, Grant Schoenebeck:
Relaxing Common Belief for Social Networks. ITCS 2021: 45:1-45:20 - [c48]Grant Schoenebeck, Fang-Yi Yu:
Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach. ITCS 2021: 78:1-78:20 - [c47]Grant Schoenebeck, Biaoshuai Tao:
Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences. NeurIPS 2021: 1872-1883 - [c46]Shih-Tang Su, Vijay G. Subramanian, Grant Schoenebeck:
Bayesian Persuasion in Sequential Trials. WINE 2021: 22-40 - [c45]Grant Schoenebeck, Fang-Yi Yu, Yichi Zhang:
Information Elicitation from Rowdy Crowds. WWW 2021: 3974-3986 - [i39]Paul Resnick, Yuqing Kong, Grant Schoenebeck, Tim Weninger:
Survey Equivalence: A Procedure for Measuring Classifier Accuracy Against Human Labels. CoRR abs/2106.01254 (2021) - [i38]Zhihuan Huang, Shengwei Xu, You Shan, Yuxuan Lu, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck:
SURPRISE! and When to Schedule It. CoRR abs/2106.02851 (2021) - [i37]Zhihuan Huang, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck, Shengwei Xu:
BONUS! Maximizing Surprise. CoRR abs/2107.08207 (2021) - [i36]Grant Schoenebeck, Biaoshuai Tao:
Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences. CoRR abs/2108.03749 (2021) - [i35]Noah Burrell, Grant Schoenebeck:
Measurement Integrity in Peer Prediction: A Peer Assessment Case Study. CoRR abs/2108.05521 (2021) - [i34]Shih-Tang Su, Vijay G. Subramanian, Grant Schoenebeck:
Bayesian Persuasion in Sequential Trials. CoRR abs/2110.09594 (2021) - 2020
- [j7]Grant Schoenebeck, Biaoshuai Tao:
Influence Maximization on Undirected Graphs: Toward Closing the (1-1/e) Gap. ACM Trans. Economics and Comput. 8(4): 22:1-22:36 (2020) - [c44]Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao:
Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization. AAAI 2020: 590-597 - [c43]Yuqing Kong, Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu:
Information Elicitation Mechanisms for Statistical Estimation. AAAI 2020: 2095-2102 - [c42]Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu:
Limitations of Greed: Influence Maximization in Undirected Networks Re-visited. AAMAS 2020: 1224-1232 - [c41]Grant Schoenebeck, Fang-Yi Yu:
Escaping Saddle Points in Constant Dimensional Spaces: An Agent-based Modeling Perspective. EC 2020: 49-67 - [c40]Grant Schoenebeck, Fang-Yi Yu:
Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question. WINE 2020: 119-132 - [i33]Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu:
Limitations of Greed: Influence Maximization in Undirected Networks Re-visited. CoRR abs/2002.11679 (2020) - [i32]Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu:
Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization. CoRR abs/2003.10393 (2020) - [i31]Noah Burrell, Grant Schoenebeck:
Relaxing Common Belief for Social Networks. CoRR abs/2009.12936 (2020) - [i30]Grant Schoenebeck, Fang-Yi Yu:
Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach. CoRR abs/2009.14730 (2020) - [i29]Grant Schoenebeck, Chenkai Yu, Fang-Yi Yu:
Timely Information from Prediction Markets. CoRR abs/2011.03645 (2020)
2010 – 2019
- 2019
- [j6]Yuqing Kong, Grant Schoenebeck:
An Information Theoretic Framework For Designing Information Elicitation Mechanisms That Reward Truth-telling. ACM Trans. Economics and Comput. 7(1): 2:1-2:33 (2019) - [j5]Grant Schoenebeck, Biaoshuai Tao:
Beyond Worst-case (In)approximability of Nonsubmodular Influence Maximization. ACM Trans. Comput. Theory 11(3): 12:1-12:56 (2019) - [c39]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 - [c38]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 - [c37]Grant Schoenebeck, Biaoshuai Tao:
Influence Maximization on Undirected Graphs: Towards Closing the (1-1/e) Gap. EC 2019: 423-453 - [c36]Shih-Tang Su, Vijay G. Subramanian, Grant Schoenebeck:
Social learning with questions. NetEcon@SIGMETRICS 2019: 9:1 - [c35]Yuqing Kong, Chris Peikert, Grant Schoenebeck, Biaoshuai Tao:
Outsourcing Computation: The Minimal Refereed Mechanism. WINE 2019: 256-270 - [i28]Yuqing Kong, Chris Peikert, Grant Schoenebeck, Biaoshuai Tao:
Outsourcing Computation: the Minimal Refereed Mechanism. CoRR abs/1910.14269 (2019) - [i27]Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao:
Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization. CoRR abs/1911.08164 (2019) - 2018
- [j4]Boyu Tian, Jiamin Huang, Barzan Mozafari, Grant Schoenebeck:
Contention-Aware Lock Scheduling for Transactional Databases. Proc. VLDB Endow. 11(5): 648-662 (2018) - [c34]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 - [c33]Yuqing Kong, Grant Schoenebeck:
Equilibrium Selection in Information Elicitation without Verification via Information Monotonicity. ITCS 2018: 13:1-13:20 - [c32]Yuqing Kong, Grant Schoenebeck:
Optimizing Bayesian Information Revelation Strategy in Prediction Markets: the Alice Bob Alice Case. ITCS 2018: 14:1-14:20 - [c31]Yuqing Kong, Grant Schoenebeck:
Water from Two Rocks: Maximizing the Mutual Information. EC 2018: 177-194 - [c30]Yuqing Kong, Grant Schoenebeck:
Eliciting Expertise without Verification. EC 2018: 195-212 - [c29]Grant Schoenebeck, Fang-Yi Yu:
Consensus of Interacting Particle Systems on Erdös-Rényi Graphs. SODA 2018: 1945-1964 - [i26]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 abs/1801.02613 (2018) - [i25]Yuqing Kong, Grant Schoenebeck:
Eliciting Expertise without Verification. CoRR abs/1802.08312 (2018) - [i24]Yuqing Kong, Grant Schoenebeck:
Water from Two Rocks: Maximizing the Mutual Information. CoRR abs/1802.08887 (2018) - [i23]Grant Schoenebeck, Shih-Tang Su, Vijay G. Subramanian:
Social Learning with Questions. CoRR abs/1811.00226 (2018) - 2017
- [j3]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): 201-214 (2017) - [c28]Jie Gao, Bo Li, Grant Schoenebeck, Fang-Yi Yu:
Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents. AAAI 2017: 537-543 - [c27]Jiamin Huang, Barzan Mozafari, Grant Schoenebeck, Thomas F. Wenisch:
A Top-Down Approach to Achieving Performance Predictability in Database Systems. SIGMOD Conference 2017: 745-758 - [c26]Rico Angell, Grant Schoenebeck:
Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization. WINE 2017: 16-29 - [c25]Grant Schoenebeck, Biaoshuai Tao:
Beyond Worst-Case (In)approximability of Nonsubmodular Influence Maximization. WINE 2017: 368-382 - [c24]Jie Gao, Grant Schoenebeck, Fang-Yi Yu:
Cascades and Myopic Routing in Nonhomogeneous Kleinberg's Small World Model. WINE 2017: 383-394 - [i22]Grant Schoenebeck, Biaoshuai Tao:
Beyond Worst-Case (In)approximability of Nonsubmodular Influence Maximization. CoRR abs/1710.02827 (2017) - 2016
- [c23]Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck, Fang-Yi Yu:
General Threshold Model for Social Cascades: Analysis and Simulations. EC 2016: 617-634 - [c22]Grant Schoenebeck, Aaron Snook, Fang-Yi Yu:
Sybil Detection Using Latent Network Structure. EC 2016: 739-756 - [c21]Yuqing Kong, Katrina Ligett, Grant Schoenebeck:
Putting Peer Prediction Under the Micro(economic)scope and Making Truth-Telling Focal. WINE 2016: 251-264 - [c20]Grant Schoenebeck, Fang-Yi Yu:
Complex Contagions on Configuration Model Graphs with a Power-Law Degree Distribution. WINE 2016: 459-472 - [i21]Yuqing Kong, Grant Schoenebeck, Katrina Ligett:
Putting Peer Prediction Under the Micro(economic)scope and Making Truth-telling Focal. CoRR abs/1603.07319 (2016) - [i20]Yuqing Kong, Grant Schoenebeck:
Equilibrium Selection in Information Elicitation without Verification via Information Monotonicity. CoRR abs/1603.07751 (2016) - [i19]Yuqing Kong, Grant Schoenebeck:
A Framework For Designing Information Elicitation Mechanisms That Reward Truth-telling. CoRR abs/1605.01021 (2016) - [i18]Rico Angell, Grant Schoenebeck:
Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization. CoRR abs/1609.06520 (2016) - 2015
- [c19]Roozbeh Ebrahimi, Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck:
Complex Contagions in Kleinberg's Small World Model. ITCS 2015: 63-72 - 2014
- [c18]Travis Martin, Grant Schoenebeck, Michael P. Wellman:
Characterizing strategic cascades on networks. EC 2014: 113-130 - [c17]Arpita Ghosh, Katrina Ligett, Aaron Roth, Grant Schoenebeck:
Buying private data without verification. EC 2014: 931-948 - [c16]Shiri Chechik, Daniel H. Larkin, Liam Roditty, Grant Schoenebeck, Robert Endre Tarjan, Virginia Vassilevska Williams:
Better Approximation Algorithms for the Graph Diameter. SODA 2014: 1041-1052 - [i17]Aaron Snook, Grant Schoenebeck, Paolo Codenotti:
Graph Isomorphism and the Lasserre Hierarchy. CoRR abs/1401.0758 (2014) - [i16]Roozbeh Ebrahimi, Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck:
How Complex Contagions Spread and Spread Quickly. CoRR abs/1404.2668 (2014) - [i15]Arpita Ghosh, Katrina Ligett, Aaron Roth, Grant Schoenebeck:
Buying Private Data without Verification. CoRR abs/1404.6003 (2014) - [i14]Roozbeh Ebrahimi, Jie Gao, Golnaz Ghasemiesfeh, Grant Schoenebeck:
Complex Contagions in Kleinberg's Small World Model. CoRR abs/1408.2159 (2014) - 2013
- [c15]Grant Schoenebeck:
Potential networks, contagious communities, and understanding social network structure. WWW 2013: 1123-1132 - [i13]Grant Schoenebeck:
Potential Networks, Contagious Communities, and Understanding Social Network Structure. CoRR abs/1304.1845 (2013) - [i12]Travis Martin, Grant Schoenebeck, Michael P. Wellman:
Characterizing Strategic Cascades on Networks. CoRR abs/1310.2561 (2013) - 2012
- [j2]Grant Schoenebeck, Salil P. Vadhan:
The Computational Complexity of Nash Equilibria in Concisely Represented Games. ACM Trans. Comput. Theory 4(2): 4:1-4:50 (2012) - [c14]Sanjeev Arora, Rong Ge, Sushant Sachdeva, Grant Schoenebeck:
Finding overlapping communities in social networks: toward a rigorous approach. EC 2012: 37-54 - [c13]Aaron Roth, Grant Schoenebeck:
Conducting truthful surveys, cheaply. EC 2012: 826-843 - [i11]Aaron Roth, Grant Schoenebeck:
Conducting Truthful Surveys, Cheaply. CoRR abs/1203.0353 (2012) - 2011
- [c12]Thomas Holenstein, Grant Schoenebeck:
General Hardness Amplification of Predicates and Puzzles - (Extended Abstract). TCC 2011: 19-36 - [c11]Rafael M. Frongillo, Grant Schoenebeck, Omer Tamuz:
Social Learning in a Changing World. WINE 2011: 146-157 - [i10]Rafael M. Frongillo, Grant Schoenebeck, Omer Tamuz:
Social Learning in a Changing World. CoRR abs/1109.5482 (2011) - [i9]Sanjeev Arora, Rong Ge, Sushant Sachdeva, Grant Schoenebeck:
Finding Overlapping Communities in Social Networks: Toward a Rigorous Approach. CoRR abs/1112.1831 (2011) - 2010
- [b1]Grant Robert Schoenebeck:
Limitations of Linear and Semidefinite Programs. University of California, Berkeley, USA, 2010 - [j1]Sarita Yardi, Daniel M. Romero, Grant Schoenebeck, danah boyd:
Detecting Spam in a Twitter Network. First Monday 15(1) (2010) - [c10]Arnab Bhattacharyya, Swastik Kopparty, Grant Schoenebeck, Madhu Sudan, David Zuckerman:
Optimal Testing of Reed-Muller Codes. FOCS 2010: 488-497 - [c9]Elchanan Mossel, Grant Schoenebeck:
Reaching Consensus on Social Networks. ICS 2010: 214-229 - [c8]Anupam Gupta, Aaron Roth, Grant Schoenebeck, Kunal Talwar:
Constrained Non-monotone Submodular Maximization: Offline and Secretary Algorithms. WINE 2010: 246-257 - [p1]Arnab Bhattacharyya, Swastik Kopparty, Grant Schoenebeck, Madhu Sudan, David Zuckerman:
Optimal Testing of Reed-Muller Codes. Property Testing 2010: 269-275 - [i8]Thomas Holenstein, Grant Schoenebeck:
General Hardness Amplification of Predicates and Puzzles. CoRR abs/1002.3534 (2010) - [i7]Anupam Gupta, Aaron Roth, Grant Schoenebeck, Kunal Talwar:
Constrained Non-Monotone Submodular Maximization: Offline and Secretary Algorithms. CoRR abs/1003.1517 (2010)
2000 – 2009
- 2009
- [c7]Constantinos Daskalakis, Grant Schoenebeck, Gregory Valiant, Paul Valiant:
On the complexity of Nash equilibria of action-graph games. SODA 2009: 710-719 - [i6]Arnab Bhattacharyya, Swastik Kopparty, Grant Schoenebeck, Madhu Sudan, David Zuckerman:
Optimal Testing of Reed-Muller Codes. CoRR abs/0910.0641 (2009) - [i5]Arnab Bhattacharyya, Swastik Kopparty, Grant Schoenebeck, Madhu Sudan, David Zuckerman:
Optimal testing of Reed-Muller codes. Electron. Colloquium Comput. Complex. TR09 (2009) - 2008
- [c6]Grant Schoenebeck:
Linear Level Lasserre Lower Bounds for Certain k-CSPs. FOCS 2008: 593-602 - [i4]Constantinos Daskalakis, Grant Schoenebeck, Gregory Valiant, Paul Valiant:
On the Complexity of Nash Equilibria of Action-Graph Games. CoRR abs/0802.1604 (2008) - 2007
- [c5]Grant Schoenebeck, Luca Trevisan, Madhur Tulsiani:
A Linear Round Lower Bound for Lovasz-Schrijver SDP Relaxations of Vertex Cover. CCC 2007: 205-216 - [c4]Grant Schoenebeck, Luca Trevisan, Madhur Tulsiani:
Tight integrality gaps for Lovasz-Schrijver LP relaxations of vertex cover and max cut. STOC 2007: 302-310 - 2006
- [c3]Halldor Isak Gylfason, Omar Khan, Grant Schoenebeck:
CHORA: Expert-Based P2P Web Search. AP2PC 2006: 74-85 - [c2]Grant Schoenebeck, Salil P. Vadhan:
The computational complexity of nash equilibria in concisely represented games. EC 2006: 270-279 - [i3]Grant Schoenebeck, Luca Trevisan, Madhur Tulsiani:
A Linear Round Lower Bound for Lovasz-Schrijver SDP Relaxations of Vertex Cover. Electron. Colloquium Comput. Complex. TR06 (2006) - [i2]Grant Schoenebeck, Luca Trevisan, Madhur Tulsiani:
Tight Integrality Gaps for Lovasz-Schrijver LP Relaxations of Vertex Cover and Max Cut. Electron. Colloquium Comput. Complex. TR06 (2006) - 2005
- [i1]Grant Schoenebeck, Salil P. Vadhan:
The Computational Complexity of Nash Equilibria in Concisely Represented Games. Electron. Colloquium Comput. Complex. TR05 (2005) - 2004
- [c1]David C. Parkes, Grant Schoenebeck:
GROWRANGE: Anytime VCG-Based Mechanisms. AAAI 2004: 34-41
Coauthor Index
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