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ProportionNet: Balancing Fairness and Revenue for Auction Design with
  Deep Learning

ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning

13 October 2020
Kevin Kuo
Anthony Ostuni
Elizabeth Horishny
Michael J. Curry
Samuel Dooley
Ping Yeh-Chiang
Tom Goldstein
John P. Dickerson
ArXivPDFHTML

Papers citing "ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning"

5 / 5 papers shown
Title
LLM-Powered Preference Elicitation in Combinatorial Assignment
LLM-Powered Preference Elicitation in Combinatorial Assignment
Ermis Soumalias
Yanchen Jiang
Kehang Zhu
Michael J. Curry
Sven Seuken
David C. Parkes
79
0
0
14 Feb 2025
The Bandit Whisperer: Communication Learning for Restless Bandits
The Bandit Whisperer: Communication Learning for Restless Bandits
Yunfan Zhao
Tonghan Wang
Dheeraj M. Nagaraj
Aparna Taneja
Milind Tambe
78
5
0
11 Aug 2024
Auction learning as a two-player game
Auction learning as a two-player game
Jad Rahme
Samy Jelassia
Matthew Weinberga
31
45
0
10 Jun 2020
Facebook's Advertising Platform: New Attack Vectors and the Need for
  Interventions
Facebook's Advertising Platform: New Attack Vectors and the Need for Interventions
Irfan Faizullabhoy
Aleksandra Korolova
35
35
0
27 Mar 2018
Certifying and removing disparate impact
Certifying and removing disparate impact
Michael Feldman
Sorelle A. Friedler
John Moeller
C. Scheidegger
Suresh Venkatasubramanian
FaML
129
1,978
0
11 Dec 2014
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