Feng, Zhe
Bibliographic References tagged with Feng, Zhe
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P. Duetting, Z. Feng, H. Narasimhan, D. C. Parkes, and S. S. Ravindranath,
“Optimal Auctions through Deep Learning: Advances in Differentiable Economics. ”, J. ACM , vol. 71, no. (1), pp. 5:1–5:53, 2024.
P. Duetting, Z. Feng, H. Narasimhan, D. C. Parkes, and S. S. Ravindranath,
“Optimal Auctions through Deep Learning: Advances in Differentiable Economics. ”, J. ACM , vol. 71, no. (1), pp. 5:1–5:53, 2024.
S. S. Ravindranath, Z. Feng, S. Li, J. Ma, S. D. Kominers, and D. C. Parkes,
“Deep Learning for Two-Sided Matching.”, in 6th workshop in an interdisciplinary and international workshop series on matching under preferences, Vienna, Austria, 2022.
S. S. Ravindranath, Z. Feng, S. Li, J. Ma, S. D. Kominers, and D. C. Parkes,
“Deep Learning for Two-Sided Matching.”, in 6th workshop in an interdisciplinary and international workshop series on matching under preferences, Vienna, Austria, 2022.
V. Conitzer, Z. Feng, D. C. Parkes, and E. Sodomka,
“Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss”, Proceedings 17th Conference on Web and Internet Economics (WINE), 2021, pp. 76–94.
V. Conitzer, Z. Feng, D. C. Parkes, and E. Sodomka,
“Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss”, Proceedings 17th Conference on Web and Internet Economics (WINE), 2021, pp. 76–94.
Z. Feng, D. C. Parkes, and S. S. Ravindranath,
“Machine Learning for Matching Markets”, in Online matching theory and market design, N. Immorlica, F. Echenique, and V. Vazirani (eds), Cambridge University Press , 2022.
Z. Feng, D. C. Parkes, and S. S. Ravindranath,
“Machine Learning for Matching Markets”, in Online matching theory and market design, N. Immorlica, F. Echenique, and V. Vazirani (eds), Cambridge University Press , 2022.
P. Duetting, Z. Feng, H. Narasimhan, D. C. Parkes, and S. S. Ravindranath,
“Optimal auctions through deep learning”, Communications of the ACM, vol. 64, no. 8, pp. 109–116, 2021.
P. Duetting, Z. Feng, H. Narasimhan, D. C. Parkes, and S. S. Ravindranath,
“Optimal auctions through deep learning”, Communications of the ACM, vol. 64, no. 8, pp. 109–116, 2021.
P. Duetting, Z. Feng, H. Narasimham, D. C. Parkes, and S. S. Ravindranath,
“Optimal Auctions through Deep Learning”, in Proceedings of the 36th International Conference on Machine Learning (ICML’19), 2019, pp. 1706–1715.
P. Duetting, Z. Feng, H. Narasimham, D. C. Parkes, and S. S. Ravindranath,
“Optimal Auctions through Deep Learning”, in Proceedings of the 36th International Conference on Machine Learning (ICML’19), 2019, pp. 1706–1715.
Z. Feng, H. Narasimhan, and D. C. Parkes,
“Deep Learning for Revenue-Optimal Auctions with Budgets”, in Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems. (AAMAS 2018), 2018, pp. 354–362.
Z. Feng, H. Narasimhan, and D. C. Parkes,
“Deep Learning for Revenue-Optimal Auctions with Budgets”, in Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems. (AAMAS 2018), 2018, pp. 354–362.
P. Duetting, Z. Feng, H. Narasimhan, and D. C. Parkes,
“Optimal Economic Design through Deep Learning”, in Proc. of the NIPS Workshop on "Learning in the Presence of Strategic Behavior", Long Beach, CA, 2017.
P. Duetting, Z. Feng, H. Narasimhan, and D. C. Parkes,
“Optimal Economic Design through Deep Learning”, in Proc. of the NIPS Workshop on "Learning in the Presence of Strategic Behavior", Long Beach, CA, 2017.
Z. Feng, D. C. Parkes, and H. Xu,
“The intrinsic robustness of stochastic bandits to strategic manipulation.”, in Proceedings of the 37th International Conference on Machine Learning, ICML ’20, Proceedings of Machine Learning Research, 2020, pp. 3092–3101.
Z. Feng, D. C. Parkes, and H. Xu,
“The intrinsic robustness of stochastic bandits to strategic manipulation.”, in Proceedings of the 37th International Conference on Machine Learning, ICML ’20, Proceedings of Machine Learning Research, 2020, pp. 3092–3101.