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AIQ

AIQ

by Polson, Nick, James G. Scott

Human-machine systemsArtificial intelligenceAutomation
4.0
Open Library
Open Library

Themes & subjects

Human-machine systemsArtificial intelligenceAutomation

About the authors

Polson, Nick

7 May 1963

British statistician who is a professor of econometrics and statistics at the University of Chicago Booth School of Business-Wikipedia

James G. Scott

statistical methodology for high-dimensional data sets, with applications in a diverse set of areas spanning the social, physical, and biomedical sciences. Three areas of methodological focus include (1) large-scale multiple testing, anomaly-detection and screening problems, where the rate of false discoveries must be controlled in order to yield viable inferences; (2) inference in sparse models; and (3) the application of data-augmentation theory and algorithms to improve the efficiency of Bayesian inference in large-scale models for discrete data sets.-faculty profile

Authors

Polson, Nick, James G. Scott

Pages

272

Read time

≈ 7h

Editions

6

Language

English

Publisher

Transworld Publishers Limited

ISBN

9781250182166

Where to buy

TR
Amazon Bookshop

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