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We study the connection between multicalibration and boosting for squared error regression.
On the uniform convergence of relative frequencies of events to their probabilities, 1971
V.N. Vapnik and A. YA. Chervonenkis · 1971
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The well-calibrated bayesian
A Philip Dawid · 1982
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On learning sets and functions
Balas K Natarajan · 1989
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The strength of weak learnability
Robert E Schapire · 1990
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A decision-theoretic generalization of on-line learning and an application to boosting
Yoav Freund and Robert E Schapire · 1997
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Regret in the on-line decision problem
Dean P Foster and Rakesh Vohra · 1999
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Greedy function approximation: a gradient boosting machine
Jerome H Friedman · 2001
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Boosting methods for regression
Nigel Duffy and David Helmbold · 2002
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Learning monotonic linear functions
Adam Kalai · 2004
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From external to internal regret
Avrim Blum and Yishay Mansour · 2005
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Agnostically learning halfspaces
Adam Tauman Kalai, Adam R Klivans, Yishay Mansour, and Rocco A Servedio · 2008
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Potential-based agnostic boosting
Varun Kanade and Adam Kalai · 2009
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Convergence of stochastic processes
David Pollard · 2012
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Boosting: Foundations and algorithms
Robert E Schapire and Yoav Freund · 2013
Cited alongside, same era.
Understanding machine learning: From theory to algorithms
Shai Shalev-Shwartz and Shai Ben-David · 2014
Cited alongside, same era.
Multicalibration: Calibration for the (computationally-identifiable) masses
Sample complexity of uniform convergence for multicalibration
Eliran Shabat, Lee Cohen, and Yishay Mansour · 2020
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Maya Burhanpurkar, Zhun Deng, Cynthia Dwork, and Linjun Zhang · 2021
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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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Moment multicalibration for uncertainty estimation
Christopher Jung, Changhwa Lee, Mallesh Pai, Aaron Roth, and Rakesh Vohra · 2021
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Omnipredictors
Parikshit Gopalan, Adam Tauman Kalai, Omer Reingold, Vatsal Sharan, and Udi Wieder · 2022
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Ursula Hébert-Johnson, Michael Kim, Omer Reingold, and Guy Rothblum · 2018
Cited alongside, same era.
Multiaccuracy: Black-box post-processing for fairness in classification
Michael P Kim, Amirata Ghorbani, and James Zou · 2019
Cited alongside, same era.
Christopher Jung, Georgy Noarov, Ramya Ramalingam, and Aaron Roth · 2022
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Universal adaptability: Target-independent inference that competes with propensity scoring
Michael P Kim, Christoph Kern, Shafi Goldwasser, Frauke Kreuter, and Omer Reingold · 2022
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Uncertain: Modern topics in uncertainty estimation
Aaron Roth · 2022
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