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Oh the Prices You'll See: Designing a Fair Exchange System to Mitigate Personalized Pricing

4 September 2024

Papers citing "Oh the Prices You'll See: Designing a Fair Exchange System to Mitigate Personalized Pricing"

20 / 20 papers shown

Title
Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness Seamus Somerstep Yaácov Ritov Yuekai Sun FaML 79 4 0 30 May 2024
Learning and Collusion in Multi-unit Auctions Simina Brânzei Mahsa Derakhshan Negin Golrezaei Yanjun Han 43 3 0 27 May 2023
Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness Edward A. Small Kacper Sokol Daniel Manning Flora D. Salim Jeffrey Chan FaML 81 8 0 19 Apr 2023
Algorithmic Collective Action in Machine Learning Moritz Hardt Eric Mazumdar Celestine Mendler-Dünner Tijana Zrnic 36 22 0 08 Feb 2023
A Fair Pricing Model via Adversarial Learning Vincent Grari Arthur Charpentier Marcin Detyniecki 53 14 0 24 Feb 2022
Regulatory Instruments for Fair Personalized Pricing Renzhe Xu Xingxuan Zhang Pengbi Cui Yangqiu Song Zheyan Shen Jiazheng Xu 59 15 0 09 Feb 2022
Improving Fairness via Federated Learning Yuchen Zeng Hongxu Chen Kangwook Lee FedML 73 64 0 29 Oct 2021
GIFAIR-FL: A Framework for Group and Individual Fairness in Federated Learning Xubo Yue Maher Nouiehed Raed Al Kontar FedML 71 37 0 05 Aug 2021
Fairness, Welfare, and Equity in Personalized Pricing Nathan Kallus Angela Zhou 54 40 0 21 Dec 2020
Fairness and Accuracy in Federated Learning Wei Huang Tianrui Li Dexian Wang Shengdong Du Junbo Zhang FedML 94 56 0 18 Dec 2020
Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation Kate Donahue Jon M. Kleinberg FedML 71 81 0 02 Oct 2020
Collaborative Fairness in Federated Learning Lingjuan Lyu Xinyi Xu Qian Wang FedML 68 193 0 27 Aug 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 61 341 0 14 Feb 2020
Fair Regression: Quantitative Definitions and Reduction-based Algorithms Alekh Agarwal Miroslav Dudík Zhiwei Steven Wu FaML 59 248 0 30 May 2019
Fair Resource Allocation in Federated Learning Tian Li Maziar Sanjabi Ahmad Beirami Virginia Smith FedML 190 804 0 25 May 2019
Fair Algorithms for Clustering Suman Kalyan Bera Deeparnab Chakrabarty Nicolas J. Flores Maryam Negahbani FaML FedML 73 241 0 08 Jan 2019
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 227 1,103 0 06 Mar 2018
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 224 1,586 0 20 Mar 2017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 205 1,213 0 26 Oct 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,593 0 17 Feb 2016