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Recommendations as Treatments: Debiasing Learning and Evaluation

Recommendations as Treatments: Debiasing Learning and Evaluation

17 February 2016
Tobias Schnabel
Adith Swaminathan
Ashudeep Singh
Navin Chandak
Thorsten Joachims
    CML
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Papers citing "Recommendations as Treatments: Debiasing Learning and Evaluation"

8 / 108 papers shown
Title
Causal Inference with Noisy and Missing Covariates via Matrix
  Factorization
Causal Inference with Noisy and Missing Covariates via Matrix Factorization
Nathan Kallus
Xiaojie Mao
Madeleine Udell
CML
14
62
0
03 Jun 2018
Counterfactual Mean Embeddings
Counterfactual Mean Embeddings
Krikamol Muandet
Motonobu Kanagawa
Sorawit Saengkyongam
S. Marukatat
CML
OffRL
29
39
0
22 May 2018
Active Learning with Logged Data
Active Learning with Logged Data
Songbai Yan
Kamalika Chaudhuri
T. Javidi
40
27
0
25 Feb 2018
Prophit: Causal inverse classification for multiple continuously valued
  treatment policies
Prophit: Causal inverse classification for multiple continuously valued treatment policies
Michael T. Lash
Qihang Lin
W. Street
CML
13
3
0
14 Feb 2018
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
314
0
30 Oct 2017
Human Interaction with Recommendation Systems
Human Interaction with Recommendation Systems
S. Schmit
C. Riquelme
21
51
0
01 Mar 2017
Unbiased Learning-to-Rank with Biased Feedback
Unbiased Learning-to-Rank with Biased Feedback
Thorsten Joachims
Adith Swaminathan
Tobias Schnabel
CML
17
538
0
16 Aug 2016
Unbiased Comparative Evaluation of Ranking Functions
Unbiased Comparative Evaluation of Ranking Functions
Tobias Schnabel
Adith Swaminathan
P. Frazier
Thorsten Joachims
16
27
0
25 Apr 2016
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