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pro vyhledávání: '"Mullins, Brett"'
Autor:
Mullins, Brett, Fuentes, Miguel, Xiao, Yingtai, Kifer, Daniel, Musco, Cameron, Sheldon, Daniel
Differential privacy is the dominant standard for formal and quantifiable privacy and has been used in major deployments that impact millions of people. Many differentially private algorithms for query release and synthetic data contain steps that re
Externí odkaz:
http://arxiv.org/abs/2410.01091
Mechanisms for generating differentially private synthetic data based on marginals and graphical models have been successful in a wide range of settings. However, one limitation of these methods is their inability to incorporate public data. Initiali
Externí odkaz:
http://arxiv.org/abs/2403.07797
Autor:
Mullins, Brett
Rule-based explanations provide simple reasons explaining the behavior of machine learning classifiers at given points in the feature space. Several recent methods (Anchors, LORE, etc.) purport to generate rule-based explanations for arbitrary or bla
Externí odkaz:
http://arxiv.org/abs/2301.09042
We propose AIM, a new algorithm for differentially private synthetic data generation. AIM is a workload-adaptive algorithm within the paradigm of algorithms that first selects a set of queries, then privately measures those queries, and finally gener
Externí odkaz:
http://arxiv.org/abs/2201.12677
Autor:
Mullins, Brett
We introduce the notion of pointwise coverage to measure the explainability properties of machine learning classifiers. An explanation for a prediction is a definably simple region of the feature space sharing the same label as the prediction, and th
Externí odkaz:
http://arxiv.org/abs/1910.08595
Autor:
Mullins, Brett1 (AUTHOR), Sjoquist, David L.2 (AUTHOR), Wallace, Sally3 (AUTHOR) swallace@gsu.edu
Publikováno v:
Social Science Quarterly (Wiley-Blackwell). Nov2021, Vol. 102 Issue 6, p2718-2732. 15p. 4 Charts, 3 Graphs.
Publikováno v:
Proceedings. Annual Conference on Taxation and Minutes of the Annual Meeting of the National Tax Association, 2014 Jan 01. 107, 1-34.
Externí odkaz:
https://www.jstor.org/stable/26812265
Autor:
Mullins, Brett
Publikováno v:
Economics Honors Theses.
As a central tenet of falsificationism, Karl Popper holds that all possible scientific theories individually have a probability equal to zero. Popper’s position rests upon the Principle of Indifference, the equiprobability of mutually exclusive out
Externí odkaz:
http://scholarworks.gsu.edu/econ_hontheses/1
http://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1000&context=econ_hontheses
http://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1000&context=econ_hontheses
Akademický článek
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Autor:
Mullins, Brett
As a central tenet of falsificationism, Karl Popper holds that all possible scientific theories individually have a probability equal to zero. Popper’s position rests upon the Principle of Indifference, the equiprobability of mutually exclusive out
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06ff56a114822b03a601b9d5e9d8102b