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Breaking Feedback Loops in Recommender Systems with Causal Inference

Breaking Feedback Loops in Recommender Systems with Causal Inference

4 July 2022
K. Krauth
Yixin Wang
Michael I. Jordan
    CML
ArXivPDFHTML

Papers citing "Breaking Feedback Loops in Recommender Systems with Causal Inference"

4 / 4 papers shown
Title
Tackling Interference Induced by Data Training Loops in A/B Tests: A
  Weighted Training Approach
Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach
Nian Si
11
4
0
26 Oct 2023
Performative Prediction with Neural Networks
Performative Prediction with Neural Networks
Mehrnaz Mofakhami
Ioannis Mitliagkas
Gauthier Gidel
40
16
0
14 Apr 2023
Causal Inference out of Control: Estimating the Steerability of
  Consumption
Causal Inference out of Control: Estimating the Steerability of Consumption
Gary Cheng
Moritz Hardt
Celestine Mendler-Dünner
CML
37
1
0
10 Feb 2023
How Algorithmic Confounding in Recommendation Systems Increases
  Homogeneity and Decreases Utility
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility
A. Chaney
Brandon M Stewart
Barbara E. Engelhardt
CML
169
313
0
30 Oct 2017
1