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1806.00543
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The Externalities of Exploration and How Data Diversity Helps Exploitation
1 June 2018
Manish Raghavan
Aleksandrs Slivkins
Jennifer Wortman Vaughan
Zhiwei Steven Wu
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Papers citing
"The Externalities of Exploration and How Data Diversity Helps Exploitation"
13 / 13 papers shown
Title
Bandit Social Learning: Exploration under Myopic Behavior
Kiarash Banihashem
Mohammadtaghi Hajiaghayi
Suho Shin
Aleksandrs Slivkins
263
4
0
15 Feb 2023
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers
Ananth Balashankar
Alyssa Lees
Chris Welty
L. Subramanian
51
21
0
30 Oct 2019
Fair Personalization
L. E. Celis
Nisheeth K. Vishnoi
FaML
38
17
0
07 Jul 2017
Calibrated Fairness in Bandits
Yang Liu
Goran Radanović
Christos Dimitrakakis
Debmalya Mandal
David C. Parkes
FedML
FaML
40
89
0
06 Jul 2017
Competing Bandits: Learning under Competition
Yishay Mansour
Aleksandrs Slivkins
Zhiwei Steven Wu
85
42
0
27 Feb 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
295
2,098
0
24 Oct 2016
Equality of Opportunity in Supervised Learning
Moritz Hardt
Eric Price
Nathan Srebro
FaML
161
4,276
0
07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon M. Kleinberg
S. Mullainathan
Manish Raghavan
FaML
94
1,762
0
19 Sep 2016
Fairness in Learning: Classic and Contextual Bandits
Matthew Joseph
Michael Kearns
Jamie Morgenstern
Aaron Roth
FaML
55
473
0
23 May 2016
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal
Daniel J. Hsu
Satyen Kale
John Langford
Lihong Li
Robert Schapire
OffRL
275
504
0
04 Feb 2014
The Convex Geometry of Linear Inverse Problems
V. Chandrasekaran
Benjamin Recht
P. Parrilo
A. Willsky
177
1,338
0
03 Dec 2010
Nonparametric Bandits with Covariates
Philippe Rigollet
A. Zeevi
181
109
0
08 Mar 2010
A Contextual-Bandit Approach to Personalized News Article Recommendation
Lihong Li
Wei Chu
John Langford
Robert Schapire
351
2,935
0
28 Feb 2010
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