Fairness in Recommendation: Foundations, Methods and Applications

Fairness in Recommendation: Foundations, Methods and Applications

26 May 2022

Juntao Tan

Papers citing "Fairness in Recommendation: Foundations, Methods and Applications"

10 / 10 papers shown

Title
Recommending the right academic programs: An interest mining approach using BERTopic Alessandro Hill Kalen Goo Puneet Agarwal 38 0 0 11 Jan 2025
dsld: A Socially Relevant Tool for Teaching Statistics Taha Abdullah Arjun Ashok Brandon Estrada Norman Matloff Aditya Mittal Norman Matloff Aditya Mittal 21 0 0 06 Nov 2024
Unveiling Bias in Fairness Evaluations of Large Language Models: A Critical Literature Review of Music and Movie Recommendation Systems Chandan Kumar Sah Xiaoli Lian Muhammad Mirajul Islam 24 7 0 08 Jan 2024
Cali3F: Calibrated Fast Fair Federated Recommendation System Zhitao Zhu Shijing Si Jianzong Wang Jing Xiao FedML 60 14 0 26 May 2022
Achieving Counterfactual Fairness for Causal Bandit Wen Huang Lu Zhang Xintao Wu CML 87 22 0 21 Sep 2021
User Tampering in Reinforcement Learning Recommender Systems Charles Evans Atoosa Kasirzadeh OffRL AAML 73 39 0 09 Sep 2021
User-oriented Fairness in Recommendation Yunqi Li H. Chen Zuohui Fu Yingqiang Ge Yongfeng Zhang FaML 96 228 0 21 Apr 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 107 87 0 05 Feb 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 286 4,143 0 23 Aug 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 185 2,079 0 24 Oct 2016