| Optimal auctions through deep learning P Dütting, Z Feng, H Narasimhan, D Parkes, SS Ravindranath International Conference on Machine Learning, 1706-1715, 2019 | 156 | 2019 |
| Deep learning for revenue-optimal auctions with budgets Z Feng, H Narasimhan, DC Parkes Proceedings of the 17th International Conference on Autonomous Agents and …, 2018 | 58 | 2018 |
| Learning to bid without knowing your value Z Feng, C Podimata, V Syrgkanis Proceedings of the 2018 ACM Conference on Economics and Computation, 505-522, 2018 | 38 | 2018 |
| Understanding PPA-completeness X Deng, JR Edmonds, Z Feng, Z Liu, Q Qi, Z Xu Journal of Computer and System Sciences 115, 146-168, 2021 | 22 | 2021 |
| Online learning for measuring incentive compatibility in ad auctions? Z Feng, O Schrijvers, E Sodomka The World Wide Web Conference, 2729-2735, 2019 | 20 | 2019 |
| Octahedral Tucker is PPA-Complete. X Deng, Z Feng, R Kulkarni Electron. Colloquium Comput. Complex. 24, 118, 2017 | 19 | 2017 |
| The intrinsic robustness of stochastic bandits to strategic manipulation Z Feng, D Parkes, H Xu International Conference on Machine Learning, 3092-3101, 2020 | 18 | 2020 |
| An adaptive independence sampler MCMC algorithm for Bayesian inferences of functions Z Feng, J Li SIAM Journal on Scientific Computing 40 (3), A1301-A1321, 2018 | 12* | 2018 |
| Convergence analysis of no-regret bidding algorithms in repeated auctions Z Feng, G Guruganesh, C Liaw, A Mehta, A Sethi Proceedings of the AAAI Conference on Artificial Intelligence 35 (6), 5399-5406, 2021 | 9 | 2021 |
| Reserve Price Optimization for First Price Auctions in Display Advertising Z Feng, S Lahaie, J Schneider, J Ye International Conference on Machine Learning, 3230-3239, 2021 | 4* | 2021 |
| Optimal auctions through deep learning P Dütting, Z Feng, H Narasimhan, DC Parkes, SS Ravindranath Communications of the ACM 64 (8), 109-116, 2021 | 3 | 2021 |
| Optimal auctions through deep learning P Dütting, Z Feng, H Narasimhan, DC Parkes, SS Ravindranath | 3 | 2020 |
| Machine learning for optimal economic design P Dütting, Z Feng, N Golowich, H Narasimhan, DC Parkes, ... The Future of Economic Design, 495-515, 2019 | 3 | 2019 |
| Welfare-Preserving -BIC to BIC Transformation with Negligible Revenue Loss V Conitzer, Z Feng, DC Parkes, E Sodomka International Conference on Web and Internet Economics, 76-94, 2021 | 2 | 2021 |
| Learning to bid in contextual first price auctions A Badanidiyuru, Z Feng, G Guruganesh arXiv preprint arXiv:2109.03173, 2021 | 2 | 2021 |
| Deep learning for two-sided matching SS Ravindranath, Z Feng, S Li, J Ma, SD Kominers, DC Parkes arXiv preprint arXiv:2107.03427, 2021 | 2 | 2021 |
| Power-law distributions in a two-sided market and net neutrality X Deng, Z Feng, CH Papadimitriou International Conference on Web and Internet Economics, 59-72, 2016 | 2 | 2016 |
| Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning J Wu, Z Zhang, Z Feng, Z Wang, Z Yang, MI Jordan, H Xu arXiv preprint arXiv:2202.10678, 2022 | 1 | 2022 |
| A Context-Integrated Transformer-Based Neural Network for Auction Design Z Duan, J Tang, Y Yin, Z Feng, X Yan, M Zaheer, X Deng arXiv preprint arXiv:2201.12489, 2022 | 1 | 2022 |
| Machine Learning-Aided Economic Design Z Feng Harvard University, 2021 | 1 | 2021 |
David C. ParkesGeorge F. Colony Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
