Log-Linear Models, Extensions, and Applications

(Part of the Neural Information Processing Series)

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Advances in training models with log-linear structures, with topics including variable selection, the geometry of neural nets, and applications.

Log-linear models play a key role in modern big data and machine learning applications. From simple binary classification models through partition functions, conditional random fields, and neural nets, log-linear structure is closely related to performance in certain applications and influences...

Format:Paperback

Language:English

ISBN:0262553465

ISBN13:9780262553469

Release Date:December 2024

Publisher:MIT Press

Length:214 Pages

Weight:1.29 lbs.

Dimensions:0.6" x 8.0" x 10.0"

Related Subjects

Computers Computers & Technology Math Mathematics Science & Math

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Log-Linear Models, Extensions, and Applications

(Part of the Neural Information Processing Series)

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