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Daniel Halpern
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Fair division with binary valuations: One rule to rule them all
D Halpern, AD Procaccia, A Psomas, N Shah
International Conference on Web and Internet Economics, 370-383, 2020
322020
Resolving the optimal metric distortion conjecture
V Gkatzelis, D Halpern, N Shah
2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020
282020
Fair division with subsidy
D Halpern, N Shah
International Symposium on Algorithmic Game Theory, 374-389, 2019
242019
Fair and efficient resource allocation with partial information
D Halpern, N Shah
arXiv preprint arXiv:2105.10064, 2021
122021
In Defense of Liquid Democracy
D Halpern, JY Halpern, A Jadbabaie, E Mossel, AD Procaccia, M Revel
arXiv preprint arXiv:2107.11868, 2021
52021
Distortion in voting with top-t preferences
A Borodin, D Halpern, M Latifian, N Shah
Proceedings of the 31st International Joint Conference on Artificial …, 2022
42022
How Many Representatives Do We Need? The Optimal Size of an Epistemic Congress
M Revel, T Lin, D Halpern
4*2022
Smoothed analysis of social choice revisited
B Flanigan, D Halpern, A Psomas
arXiv preprint arXiv:2206.14684, 2022
12022
How Many Representatives Do We Need? The Optimal Size of a Congress Voting on Binary Issues
M Revel, T Lin, D Halpern
Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 9431-9438, 2022
2022
Can Buyers Reveal for a Better Deal?
D Halpern, G Kehne, J Tucker-Foltz
arXiv preprint arXiv:2106.13882, 2021
2021
Aggregating Binary Judgments Ranked By Accuracy
D Halpern, G Kehne, D Peters, AD Procaccia, N Shah, P Skowron
Proceedings of the AAAI Conference on Artificial Intelligence 35 (6), 5456-5463, 2021
2021
Dynamic Fair Division with Partial Information
G Benadè, D Halpern, A Psomas
Liquid Democracy in Practice: An Empirical Analysis of its Epistemic Performance
M Revel, D Halpern, A Berinsky, A Jadbabaie
Unbiased Information Packets
D Halpern, A Procaccia
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Articles 1–14