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We study the problem of online prediction, in which at each time step $t$, an individual $x_t$ arrives, whose label we must predict.
Relative loss bounds for on-line density estimation with the exponential family of distributions
Katy S Azoury and Manfred K Warmuth · 2001
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Efficient algorithms for online decision problems
Adam Kalai and Santosh Vempala · 2005
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Prediction, learning, and games
Nicolo Cesa-Bianchi and Gábor Lugosi · 2006
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Medical Cost Personal Datasets — kaggle.com, 2013
Brett Lantz · 2013
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Achieving all with no parameters: Adaptive normalhedge, 2015
Haipeng Luo and Robert E. Schapire · 2015
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Efficient algorithms for adversarial contextual learning
Vasilis Syrgkanis, Akshay Krishnamurthy, and Robert Schapire · 2016
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Multicalibration: Calibration for the (computationally-identifiable) masses
Ursula Hébert-Johnson, Michael Kim, Omer Reingold, and Guy Rothblum · 2018
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Preventing fairness gerrymandering: Auditing and learning for subgroup fairness
Michael Kearns, Seth Neel, Aaron Roth, and Zhiwei Steven Wu · 2018
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Advancing subgroup fairness via sleeping experts
Avrim Blum and Thodoris Lykouris · 2019
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D030.V8.0 — IPUMS — ipums.org
Sarah Flood, Miriam King, Renae Rodgers, Steven Ruggles, and J. Robert Warren · 2020
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Retiring adult: New datasets for fair machine learning
Frances Ding, Moritz Hardt, John Miller, and Ludwig Schmidt · 2021
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Multi-group agnostic pac learnability
Guy N Rothblum and Gal Yona · 2021
Cited alongside, same era.
An algorithmic framework for bias bounties
Ira Globus-Harris, Michael Kearns, and Aaron Roth · 2022
Omnipredictors
Parikshit Gopalan, Adam Tauman Kalai, Omer Reingold, Vatsal Sharan, and Udi Wieder · 2022
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Online minimax multiobjective optimization: Multicalibeating and other applications
Daniel Lee, Georgy Noarov, Mallesh Pai, and Aaron Roth · 2022
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Simple and near-optimal algorithms for hidden stratification and multi-group learning
Christopher J Tosh and Daniel Hsu · 2022
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Oracle efficient online multicalibration and omniprediction
Sumegha Garg, Christopher Jung, Omer Reingold, and Aaron Roth · 2023
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Multicalibration as boosting for regression
Ira Globus-Harris, Declan Harrison, Michael Kearns, Aaron Roth, and Jessica Sorrell · 2023
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Loss minimization through the lens of outcome indistinguishability
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Cited alongside, same era.
Parikshit Gopalan, Lunjia Hu, Michael P Kim, Omer Reingold, and Udi Wieder · 2023
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