Fetching the paper…
Reading the bibliography…
We study an online classification problem with partial feedback in which individuals arrive one at a time from a fixed but unknown distribution, and must be classified as positive or negative.
The ellipsoid method and its consequences in combinatorial optimization
M. Grötschel, L. Lovász, and A. Schrijver · 1981
Earlier work this paper cites.
Apple tasting
David P Helmbold, Nicholas Littlestone, and Philip M Long · 2000
Earlier work this paper cites.
The nonstochastic multiarmed bandit problem
Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, and Robert E Schapire · 2002
Earlier work this paper cites.
Agnostically learning halfspaces
Adam Tauman Kalai, Adam R Klivans, Yishay Mansour, and Rocco A Servedio · 2008
Earlier work this paper cites.
Toward a classification of finite partial-monitoring games
Gábor Bartók, Dávid Pál, and Csaba Szepesvári · 2010
Earlier work this paper cites.
Three naive bayes approaches for discrimination-free classification
Toon Calders and Sicco Verwer · 2010
Earlier work this paper cites.
Contextual bandit algorithms with supervised learning guarantees
Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, and Robert Schapire · 2011
Earlier work this paper cites.
Fairness-aware learning through regularization approach
Toshihiro Kamishima, Shotaro Akaho, and Jun Sakuma · 2011
Earlier work this paper cites.
Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel · 2012
Earlier work this paper cites.
Agnostic learning of monomials by halfspaces is hard
Vitaly Feldman, Venkatesan Guruswami, Prasad Raghavendra, and Yi Wu · 2012
Cited alongside, same era.
From average case complexity to improper learning complexity
Amit Daniely, Nati Linial, and Shai Shalev-Shwartz · 2013
Cited alongside, same era.
Taming the monster: A fast and simple algorithm for contextual bandits
Alekh Agarwal, Daniel J. Hsu, Satyen Kale, John Langford, Lihong Li, and Robert E. Schapire · 2014
Cited alongside, same era.
Certifying and removing disparate impact
Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian · 2015
Cited alongside, same era.
Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, Nati Srebro, et al · 2016
Cited alongside, same era.
Fairness in learning: Classic and contextual bandits
Calibrated fairness in bandits
Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, and David C Parkes · 2017
Later among the works it cites.
A reductions approach to fair classification
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, and Hanna M. Wallach · 2018
Later among the works it cites.
Fairness in criminal justice risk assessments: The state of the art
Richard Berk, Hoda Heidari, Shahin Jabbari, Michael Kearns, and Aaron Roth · 2018
Later among the works it cites.
On preserving non-discrimination when combining expert advice
Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, and Nati Srebro · 2018
Later among the works it cites.
Two-player games for efficient non-convex constrained optimization
Andrew Cotter, Heinrich Jiang, and Karthik Sridharan · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Matthew Joseph, Michael Kearns, Jamie H Morgenstern, and Aaron Roth · 2016
Cited alongside, same era.
Inherent trade-offs in the fair determination of risk scores
Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan · 2016
Cited alongside, same era.
To predict and serve?
Kristian Lum and William Isaac · 2016
Cited alongside, same era.
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova · 2017
Cited alongside, same era.
Runaway feedback loops in predictive policing
Danielle Ensign, Sorelle A Friedler, Scott Neville, Carlos Scheidegger, and Suresh Venkatasubramanian · 2018
Later among the works it cites.
Decision making with limited feedback
Danielle Ensign, Frielder Sorelle, Neville Scott, Scheidegger Carlos, and Venkatasubramanian Suresh · 2018
Later among the works it cites.
Meritocratic fairness for infinite and contextual bandits
Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth · 2018
Later among the works it cites.