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Offline Evaluation of Reward-Optimizing Recommender Systems: The Case of
  Simulation

Offline Evaluation of Reward-Optimizing Recommender Systems: The Case of Simulation

18 September 2022
Imad Aouali
Amine Benhalloum
Martin Bompaire
Benjamin Heymann
Olivier Jeunen
D. Rohde
Otmane Sakhi
Flavian Vasile
    OffRL
ArXiv (abs)PDFHTML

Papers citing "Offline Evaluation of Reward-Optimizing Recommender Systems: The Case of Simulation"

15 / 15 papers shown
Title
Combining Reward and Rank Signals for Slate Recommendation
Combining Reward and Rank Signals for Slate Recommendation
Imad Aouali
S. Ivanov
Mike Gartrell
D. Rohde
Flavian Vasile
Victor Zaytsev
Diego Legrand
OffRL
131
4
0
26 Jul 2021
Carousel Personalization in Music Streaming Apps with Contextual Bandits
Carousel Personalization in Music Streaming Apps with Contextual Bandits
Walid Bendada
Guillaume Salha-Galvan
Théo Bontempelli
53
57
0
14 Sep 2020
BLOB : A Probabilistic Model for Recommendation that Combines Organic
  and Bandit Signals
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals
Otmane Sakhi
Stephen Bonner
D. Rohde
Flavian Vasile
65
37
0
28 Aug 2020
Counterfactual Evaluation of Slate Recommendations with Sequential
  Reward Interactions
Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions
James McInerney
B. Brost
Praveen Chandar
Rishabh Mehrotra
Ben Carterette
BDLCMLOffRL
155
56
0
25 Jul 2020
Learning from Bandit Feedback: An Overview of the State-of-the-art
Learning from Bandit Feedback: An Overview of the State-of-the-art
Olivier Jeunen
Dmytro Mykhaylov
D. Rohde
Flavian Vasile
Alexandre Gilotte
Martin Bompaire
OffRL
37
10
0
18 Sep 2019
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
107
183
0
11 Sep 2019
On the Value of Bandit Feedback for Offline Recommender System
  Evaluation
On the Value of Bandit Feedback for Offline Recommender System Evaluation
Olivier Jeunen
D. Rohde
Flavian Vasile
OffRL
45
10
0
26 Jul 2019
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural
  Recommendation Approaches
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches
Maurizio Ferrari Dacrema
Paolo Cremonesi
Dietmar Jannach
50
588
0
16 Jul 2019
Three Methods for Training on Bandit Feedback
Three Methods for Training on Bandit Feedback
Dmytro Mykhaylov
D. Rohde
Flavian Vasile
Martin Bompaire
Olivier Jeunen
OffRL
27
7
0
24 Apr 2019
Top-K Off-Policy Correction for a REINFORCE Recommender System
Top-K Off-Policy Correction for a REINFORCE Recommender System
Minmin Chen
Alex Beutel
Paul Covington
Sagar Jain
Francois Belletti
Ed H. Chi
CMLOffRL
117
482
0
06 Dec 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
Offline Evaluation of Ranking Policies with Click Models
Offline Evaluation of Ranking Policies with Click Models
Shuai Li
Yasin Abbasi-Yadkori
Branislav Kveton
S. Muthukrishnan
Vishwa Vinay
Zheng Wen
CMLOffRL
54
66
0
27 Apr 2018
Offline A/B testing for Recommender Systems
Offline A/B testing for Recommender Systems
Alexandre Gilotte
Clément Calauzènes
Thomas Nedelec
A. Abraham
Simon Dollé
OffRL
81
222
0
22 Jan 2018
Off-policy evaluation for slate recommendation
Off-policy evaluation for slate recommendation
Adith Swaminathan
A. Krishnamurthy
Alekh Agarwal
Miroslav Dudík
John Langford
Damien Jose
I. Zitouni
CMLOffRL
68
228
0
16 May 2016
Counterfactual Reasoning and Learning Systems
Counterfactual Reasoning and Learning Systems
Léon Bottou
J. Peters
J. Q. Candela
Denis Xavier Charles
D. M. Chickering
Elon Portugaly
Dipankar Ray
Patrice Y. Simard
Edward Snelson
CMLOffRL
392
787
0
11 Sep 2012
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