2024
Bibliographic References tagged with 2024
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M. Wuthrich, M. York, and D. C. Parkes,
M. Wuthrich, M. York, and D. C. Parkes,
M. H. Tessler et al.,
“AI can help humans find common ground in democratic deliberation”, Science, vol. 386, no. 6719, 2024.
M. H. Tessler et al.,
“AI can help humans find common ground in democratic deliberation”, Science, vol. 386, no. 6719, 2024.
E. Zhang et al.,
“Position: Social Environment Design Should be Further Developed for AI-based Policy-Making”, in Proc. 41st International Conference on Machine Learning, ICML 2024, 2024.
E. Zhang et al.,
“Position: Social Environment Design Should be Further Developed for AI-based Policy-Making”, in Proc. 41st International Conference on Machine Learning, ICML 2024, 2024.
L. D’Amico-Wong, Y. A. Gonczarowski, G. Q. Ma, and D. C. Parkes,
“Disrupting Bipartite Trading Networks: Matching for Revenue Maximization.”, in Proc. Twenty-Fifth ACM Conference on Economics and Computation (EC’24)., 2024.
L. D’Amico-Wong, Y. A. Gonczarowski, G. Q. Ma, and D. C. Parkes,
“Disrupting Bipartite Trading Networks: Matching for Revenue Maximization.”, in Proc. Twenty-Fifth ACM Conference on Economics and Computation (EC’24)., 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.
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.
A. Eden, G. Q. Ma, and D. C. Parkes,
“Platform Equilibrium: Analyzing Social Welfare in Online Market Places.”, in Proc. 25th Conf. on Economics and Computation (EC’24) , 2024.
A. Eden, G. Q. Ma, and D. C. Parkes,
“Platform Equilibrium: Analyzing Social Welfare in Online Market Places.”, in Proc. 25th Conf. on Economics and Computation (EC’24) , 2024.
D. Goktas et al.,
“Generative Adversarial Equilibrium Solvers.”, in The Twelfth International Conference on Learning Representations, ICLR 2024., 2024.
D. Goktas et al.,
“Generative Adversarial Equilibrium Solvers.”, in The Twelfth International Conference on Learning Representations, ICLR 2024., 2024.
O. Nahum, G. Noti, D. C. Parkes, and N. Rosenfeld,
“Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces.”, in The Twelfth International Conference on Learning Representations, ICLR 2024., 2024.
O. Nahum, G. Noti, D. C. Parkes, and N. Rosenfeld,
“Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces.”, in The Twelfth International Conference on Learning Representations, ICLR 2024., 2024.
P. Duetting, F. A. Fischer, and D. C. Parkes,
“Non-Truthful Position Auctions Are More Robust to Misspecification.”, Mathematics of Operations Research, vol. 49 , no. 2, pp. 901–927, 2024.
P. Duetting, F. A. Fischer, and D. C. Parkes,
“Non-Truthful Position Auctions Are More Robust to Misspecification.”, Mathematics of Operations Research, vol. 49 , no. 2, pp. 901–927, 2024.
I. Palacios-Huerta, D. C. Parkes, and R. Steinberg,
“Combinatorial Auctions in Practice”, Journal of Economics Literature, vol. 62 , no. 2, pp. 517–53, 2024.
I. Palacios-Huerta, D. C. Parkes, and R. Steinberg,
“Combinatorial Auctions in Practice”, Journal of Economics Literature, vol. 62 , no. 2, pp. 517–53, 2024.