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T-RECS: A Simulation Tool to Study the Societal Impact of Recommender
  Systems
v1v2 (latest)

T-RECS: A Simulation Tool to Study the Societal Impact of Recommender Systems

19 July 2021
Eli Lucherini
Matthew Sun
Amy A. Winecoff
Arvind Narayanan
ArXiv (abs)PDFHTML

Papers citing "T-RECS: A Simulation Tool to Study the Societal Impact of Recommender Systems"

15 / 15 papers shown
Title
RecSim NG: Toward Principled Uncertainty Modeling for Recommender
  Ecosystems
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
Martin Mladenov
Chih-Wei Hsu
Vihan Jain
Eugene Ie
Christopher Colby
Nicolas Mayoraz
H. Pham
Dustin Tran
Ivan Vendrov
Craig Boutilier
BDL
44
33
0
14 Mar 2021
Do Offline Metrics Predict Online Performance in Recommender Systems?
Do Offline Metrics Predict Online Performance in Recommender Systems?
K. Krauth
Sarah Dean
Alex Zhao
Wenshuo Guo
Mihaela Curmei
Benjamin Recht
Michael I. Jordan
OffRL
61
41
0
07 Nov 2020
Array Programming with NumPy
Array Programming with NumPy
Charles R. Harris
K. Millman
S. Walt
R. Gommers
Pauli Virtanen
...
Tyler Reddy
Warren Weckesser
Hameer Abbasi
C. Gohlke
T. Oliphant
156
14,986
0
18 Jun 2020
RecSim: A Configurable Simulation Platform for Recommender Systems
RecSim: A Configurable Simulation Platform for Recommender Systems
Eugene Ie
Chih-Wei Hsu
Martin Mladenov
Vihan Jain
Sanmit Narvekar
Jing Wang
Rui Wu
Craig Boutilier
105
183
0
11 Sep 2019
Degenerate Feedback Loops in Recommender Systems
Degenerate Feedback Loops in Recommender Systems
Ray Jiang
Silvia Chiappa
Tor Lattimore
András Gyorgy
Pushmeet Kohli
40
196
0
27 Feb 2019
LensKit for Python: Next-Generation Software for Recommender System
  Experiments
LensKit for Python: Next-Generation Software for Recommender System Experiments
Michael D. Ekstrand
VLM
134
82
0
10 Sep 2018
RecoGym: A Reinforcement Learning Environment for the problem of Product
  Recommendation in Online Advertising
RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising
D. Rohde
Stephen Bonner
Travis Dunlop
Flavian Vasile
Alexandros Karatzoglou
OffRL
57
150
0
02 Aug 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
211
316
0
30 Oct 2017
Beyond Parity: Fairness Objectives for Collaborative Filtering
Beyond Parity: Fairness Objectives for Collaborative Filtering
Sirui Yao
Bert Huang
FaML
40
368
0
24 May 2017
Human Interaction with Recommendation Systems
Human Interaction with Recommendation Systems
S. Schmit
C. Riquelme
58
51
0
01 Mar 2017
Joint Deep Modeling of Users and Items Using Reviews for Recommendation
Joint Deep Modeling of Users and Items Using Reviews for Recommendation
Lei Zheng
Vahid Noroozi
Philip S. Yu
HAI
153
1,002
0
17 Jan 2017
An Agent-Based Model of Message Propagation in the Facebook Electronic
  Social Network
An Agent-Based Model of Message Propagation in the Facebook Electronic Social Network
H. Nasrinpour
M. Friesen
Robert D.
R. McLeod
41
16
0
22 Nov 2016
Wide & Deep Learning for Recommender Systems
Wide & Deep Learning for Recommender Systems
Heng-Tze Cheng
L. Koc
Jeremiah Harmsen
T. Shaked
Tushar Chandra
...
Zakaria Haque
Lichan Hong
Vihan Jain
Xiaobing Liu
Hemal Shah
HAIVLM
187
3,662
0
24 Jun 2016
Collaborative Deep Learning for Recommender Systems
Collaborative Deep Learning for Recommender Systems
Hao Wang
Naiyan Wang
Dit-Yan Yeung
BDL
120
1,618
0
10 Sep 2014
BPR: Bayesian Personalized Ranking from Implicit Feedback
BPR: Bayesian Personalized Ranking from Implicit Feedback
Steffen Rendle
Christoph Freudenthaler
Zeno Gantner
Lars Schmidt-Thieme
BDL
152
5,731
0
09 May 2012
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