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Yuqing Kong
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2020 – today
- 2024
- [j2]Yuqing Kong
:
Dominantly Truthful Peer Prediction Mechanisms with a Finite Number of Tasks. J. ACM 71(2): 9:1-9:49 (2024) - [c21]Yuqi Pan
, Zhaohua Chen
, Yuqing Kong
:
Robust Decision Aggregation with Second-order Information. WWW 2024: 77-88 - [e1]Jugal Garg
, Max Klimm
, Yuqing Kong
:
Web and Internet Economics - 19th International Conference, WINE 2023, Shanghai, China, December 4-8, 2023, Proceedings. Lecture Notes in Computer Science 14413, Springer 2024, ISBN 978-3-031-48973-0 [contents] - [i33]Yongkang Guo, Jason D. Hartline, Zhihuan Huang, Yuqing Kong, Anant Shah, Fang-Yi Yu:
Algorithmic Robust Forecast Aggregation. CoRR abs/2401.17743 (2024) - [i32]Yuqing Kong:
Peer Expectation in Robust Forecast Aggregation: The Possibility/Impossibility. CoRR abs/2402.06062 (2024) - [i31]Yongkang Guo, Yuqing Kong:
Robust Decision Aggregation with Adversarial Experts. CoRR abs/2403.08222 (2024) - [i30]Yuxuan Lu, Shengwei Xu, Yichi Zhang, Yuqing Kong, Grant Schoenebeck:
Eliciting Informative Text Evaluations with Large Language Models. CoRR abs/2405.15077 (2024) - [i29]Zhihuan Huang, Yuxuan Lu, Yongkang Guo, Yuqing Kong:
How Gold to Make the Golden Snitch: Designing the "Game Changer" in Esports. CoRR abs/2405.19843 (2024) - [i28]Yuqing Kong, Shu Wang, Ying Wang:
The Surprising Benefits of Base Rate Neglect in Robust Aggregation. CoRR abs/2406.13490 (2024) - 2023
- [c20]Qian Wang
, Zongjun Yang, Xiaotie Deng, Yuqing Kong:
Learning to Bid in Repeated First-Price Auctions with Budgets. ICML 2023: 36494-36513 - [c19]Yuqing Kong, Grant Schoenebeck:
False Consensus, Information Theory, and Prediction Markets. ITCS 2023: 81:1-81:23 - [c18]Yuxuan Lu, Yuqing Kong:
Calibrating "Cheap Signals" in Peer Review without a Prior. NeurIPS 2023 - [c17]Yongkang Guo
, Yuan Yuan
, Jinshan Zhang
, Yuqing Kong
, Zhihua Zhu
, Zheng Cai
:
Near-Optimal Experimental Design Under the Budget Constraint in Online Platforms. WWW 2023: 3603-3613 - [i27]Yongkang Guo, Yuan Yuan
, Jinshan Zhang, Yuqing Kong, Zhihua Zhu, Zheng Cai:
Near-Optimal Experimental Design Under the Budget Constraint in Online Platforms. CoRR abs/2302.05005 (2023) - [i26]Qian Wang, Zongjun Yang, Xiaotie Deng, Yuqing Kong:
Learning to Bid in Repeated First-Price Auctions with Budgets. CoRR abs/2304.13477 (2023) - [i25]Yuqing Kong:
Multistable Perception, False Consensus, and Information Complements. CoRR abs/2310.11857 (2023) - [i24]Yuqi Pan, Zhaohua Chen, Yuqing Kong:
Robust Decision Aggregation with Second-order Information. CoRR abs/2311.14094 (2023) - [i23]Qian Wang, Xuanzhi Xia, Zongjun Yang, Xiaotie Deng, Yuqing Kong, Zhilin Zhang, Liang Wang, Chuan Yu, Jian Xu, Bo Zheng:
Learning against Non-credible Auctions. CoRR abs/2311.15203 (2023) - [i22]Yuxuan Lu, Yuqing Kong:
Calibrating "Cheap Signals" in Peer Review without a Prior. CoRR abs/2312.07269 (2023) - 2022
- [c16]Yuqing Kong:
More Dominantly Truthful Multi-Task Peer Prediction with a Finite Number of Tasks. ITCS 2022: 95:1-95:20 - [c15]Yuqing Kong, Yunqi Li, Yubo Zhang, Zhihuan Huang, Jinzhao Wu:
Eliciting Thinking Hierarchy without a Prior. NeurIPS 2022 - [c14]Zhihuan Huang, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck
, Shengwei Xu:
BONUS! Maximizing Surprise. WWW 2022: 36-46 - [i21]Yuqing Kong, Grant Schoenebeck:
False Consensus, Information Theory, and Prediction Markets. CoRR abs/2206.02993 (2022) - 2021
- [c13]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 - [i20]Jiale Chen, Yuqing Kong, Yuxuan Lu:
Equal Affection or Random Selection: the Quality of Subjective Feedback from a Group Perspective. CoRR abs/2102.12247 (2021) - [i19]Yuqing Kong:
Counting the Number of People That Are Less Clever Than You. CoRR abs/2103.02214 (2021) - [i18]Yongkang Guo, Zhihuan Huang, Yuqing Kong, Qian Wang:
Modularity and Mutual Information in Networks: Two Sides of the Same Coin. CoRR abs/2103.02542 (2021) - [i17]Paul Resnick
, Yuqing Kong, Grant Schoenebeck, Tim Weninger:
Survey Equivalence: A Procedure for Measuring Classifier Accuracy Against Human Labels. CoRR abs/2106.01254 (2021) - [i16]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) - [i15]Zhihuan Huang, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck, Shengwei Xu:
BONUS! Maximizing Surprise. CoRR abs/2107.08207 (2021) - [i14]Qishen Han, Sikai Ruan, Yuqing Kong, Ao Liu, Farhad Mohsin, Lirong Xia:
Truthful Information Elicitation from Hybrid Crowds. CoRR abs/2107.10119 (2021) - [i13]Yuqing Kong, Yunqi Li, Yubo Zhang, Zhihuan Huang, Jinzhao Wu:
Identifying Fast/Slow Thinking without Prior. CoRR abs/2109.10619 (2021) - [i12]Yuqing Kong:
Information Elicitation Meets Clustering. CoRR abs/2110.00952 (2021) - 2020
- [c12]Yuqing Kong, Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
:
Information Elicitation Mechanisms for Statistical Estimation. AAAI 2020: 2095-2102 - [c11]Xinwei Sun
, Yilun Xu, Peng Cao, Yuqing Kong, Lingjing Hu, Shanghang Zhang, Yizhou Wang:
TCGM: An Information-Theoretic Framework for Semi-supervised Multi-modality Learning. ECCV (3) 2020: 171-188 - [c10]Yuqing Kong:
Dominantly Truthful Multi-task Peer Prediction with a Constant Number of Tasks. SODA 2020: 2398-2411 - [i11]Xinwei Sun, Yilun Xu, Peng Cao, Yuqing Kong, Lingjing Hu, Shanghang Zhang, Yizhou Wang:
TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning. CoRR abs/2007.06793 (2020)
2010 – 2019
- 2019
- [j1]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) - [c9]Biqiao Zhang, Yuqing Kong, Georg Essl, Emily Mower Provost:
f-Similarity Preservation Loss for Soft Labels: A Demonstration on Cross-Corpus Speech Emotion Recognition. AAAI 2019: 5725-5732 - [c8]Peng Cao, Yilun Xu, Yuqing Kong, Yizhou Wang:
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds. ICLR (Poster) 2019 - [c7]Yilun Xu, Peng Cao, Yuqing Kong, Yizhou Wang:
L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise. NeurIPS 2019: 6222-6233 - [c6]Yuqing Kong
, Chris Peikert
, Grant Schoenebeck
, Biaoshuai Tao
:
Outsourcing Computation: The Minimal Refereed Mechanism. WINE 2019: 256-270 - [i10]Yuqing Kong, Yiping Ma, Yifan Wu:
Securely Trading Unverifiable Information without Trust. CoRR abs/1903.07379 (2019) - [i9]Peng Cao, Yilun Xu, Yuqing Kong, Yizhou Wang:
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds. CoRR abs/1905.13436 (2019) - [i8]Yilun Xu, Peng Cao, Yuqing Kong, Yizhou Wang:
L_DMI: An Information-theoretic Noise-robust Loss Function. CoRR abs/1909.03388 (2019) - [i7]Yuqing Kong, Chris Peikert, Grant Schoenebeck, Biaoshuai Tao:
Outsourcing Computation: the Minimal Refereed Mechanism. CoRR abs/1910.14269 (2019) - [i6]Yuqing Kong:
Dominantly Truthful Multi-task Peer Prediction with a Constant Number of Tasks. CoRR abs/1911.00272 (2019) - 2018
- [b1]Yuqing Kong:
Eliciting and Aggregating Information: An Information Theoretic Approach. University of Michigan, USA, 2018 - [c5]Yuqing Kong, Grant Schoenebeck
:
Equilibrium Selection in Information Elicitation without Verification via Information Monotonicity. ITCS 2018: 13:1-13:20 - [c4]Yuqing Kong, Grant Schoenebeck
:
Optimizing Bayesian Information Revelation Strategy in Prediction Markets: the Alice Bob Alice Case. ITCS 2018: 14:1-14:20 - [c3]Yuqing Kong, Grant Schoenebeck
:
Water from Two Rocks: Maximizing the Mutual Information. EC 2018: 177-194 - [c2]Yuqing Kong, Grant Schoenebeck
:
Eliciting Expertise without Verification. EC 2018: 195-212 - [i5]Yuqing Kong, Grant Schoenebeck:
Eliciting Expertise without Verification. CoRR abs/1802.08312 (2018) - [i4]Yuqing Kong, Grant Schoenebeck:
Water from Two Rocks: Maximizing the Mutual Information. CoRR abs/1802.08887 (2018) - 2016
- [c1]Yuqing Kong, Katrina Ligett
, Grant Schoenebeck
:
Putting Peer Prediction Under the Micro(economic)scope and Making Truth-Telling Focal. WINE 2016: 251-264 - [i3]Yuqing Kong, Grant Schoenebeck, Katrina Ligett:
Putting Peer Prediction Under the Micro(economic)scope and Making Truth-telling Focal. CoRR abs/1603.07319 (2016) - [i2]Yuqing Kong, Grant Schoenebeck:
Equilibrium Selection in Information Elicitation without Verification via Information Monotonicity. CoRR abs/1603.07751 (2016) - [i1]Yuqing Kong, Grant Schoenebeck:
A Framework For Designing Information Elicitation Mechanisms That Reward Truth-telling. CoRR abs/1605.01021 (2016)
Coauthor Index
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last updated on 2024-08-17 23:41 CEST by the dblp team
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