+86 (0)10 6276-8209
yuqing.kong
Room 202-1, Courtyard No.5 Jingyuan
Intersection of Theoretical Computer Science and Economics https://cfcs.pku.edu.cn/yuqkong/Bio-Sketch
Dr. Yuqing Kong joined Peking University in September 2018 and is currently an assistant professor at Center on Frontiers of Computing Studies, PKU. She obtained her Ph.D. degree from the Computer Science and Engineering Department at University of Michigan in 2018 and her bachelor degree in mathematics from University of Science and Technology of China in 2013. Her research interests lie in the intersection of theoretical computer science and the areas of economics: information elicitation, prediction markets, mechanism design, and the future applications of these areas to crowdsourcing and machine learning. Her papers were published in several conferences include WINE, ITCS, EC, SODA, AAAI, NeurIPS, ICLR.
Publications
2020
- Y. Kong, "Dominantly Truthful Multi-task Peer Prediction with a Constant Number of Tasks" accepted by ACM-SIAM Symposium on Discrete Algorithms (SODA), 2020.
2019
- Y. Kong, C. Peikert, G. Schoenebeck, B. Tao, "Outsourcing Computation: the Minimal Refereed Mechanism" accepted by the 15th Conference on Web and Internet Economics (WINE), 2019.
- Y. Xu*, P. Cao*, Y. Kong, Y. Wang, "LDMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise" accepted by the Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019.
- P. Cao*, Y. Xu*, Y. Kong, Y. Wang, "Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds," accepted by the 7th International Conference on Learning Representations (ICLR), 2019.
- B. Zhang*, Y. Kong*, G. Essl, E. M. Provost, "f-Similarity Preservation Loss for Soft Labels: A Demonstration on Cross-Corpus Speech Emotion Recognition," accepted by the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019.
- Y. Kong, G. Schoenebeck, "An Information Theoretic Framework For Designing Information Elicitation Mechanisms That Reward Truth-telling," accepted by the ACM Transactions on Economics and Computation (TEAC), 2019.
Publications before joining CFCS
- Y. Kong, G. Schoenebeck, "Eliciting Expertise without Verification," in proceedings of the 19th ACM Conference on Econ and Computation (EC), 195-212, Ithaca, NY, USA, June 18-22, 2018.
- Y. Kong, G. Schoenebeck, "Water from Two Rocks: Maximizing the Mutual Information," in proceedings of the 19th ACM Conference on Econ and Computation (EC), 177-194, Ithaca, NY, USA, June 18-22, 2018.
- Y. Kong, G. Schoenebeck, "Equilibrium Selection in Information Elicitation without Verification via Information Monotonicity," accepted by the 9th Innovations in Theoretical Computer Science (ITCS), Cambridge, MA, USA, January 11-14, 2018.
In LIPIcs-Leibniz International Proceedings in Informatics (Vol. 94), Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik. - Y. Kong, G. Schoenebeck, "Optimizing Bayesian Information Revelation Strategy in Prediction Markets: the Alice Bob Alice Case," accepted by the 9th Innovations in Theoretical Computer Science (ITCS), Cambridge, MA, USA, January 11-14, 2018.
In LIPIcs-Leibniz International Proceedings in Informatics (Vol. 94), Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik. - Y. Kong, K. Ligett, G. Schoenebeck, "Putting Peer Prediction Under the Micro(economic)scope and Making Truth-telling Focal," in proceedings of the 12th Conference on Web and Internet Economics (WINE), 251-264, Montreal, Canada, December 11-14, 2016.
Tutorial
- "An Information Theoretic View of Information Elicitation Mechanisms," joint organize with Grant Schoenebeck, in the 18th ACM Conference on Economics and Computation (EC), 2017.
Research Lab
Name
Yuqing Kong Research Lab
Introduction
Yuqing Kong is currently an assistant professor at the Center on Frontiers of Computing Studies (CFCS), Peking University. She obtained her Ph.D. degree from the Computer Science and Engineering Department at University of Michigan in 2018 and her bachelor degree in mathematics from University of Science and Technology of China in 2013.
Her research interests lie in the intersection of theoretical computer science and the areas of economics: information elicitation, prediction markets, mechanism design, and the future applications of these areas to crowdsourcing and machine learning. Her papers were published in several conferences include WINE, ITCS, EC, SODA, AAAI, NeurIPS, ICLR.
Link:
https://cfcs.pku.edu.cn/english/research/researchlabs/237026.htm