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Log-Linear Models, Extensions, and Applications

Log-Linear Models, Extensions, and Applications( )
Editor: Aravkin, Aleksandr
Choromanska, Anna
Deng, Li
Heigold, Georg
Jebara, Tony
Series title:Neural Information Processing Ser.
ISBN:978-0-262-03950-5
Publication Date:Nov 2018
Publisher:MIT Press
Book Format:Hardback
List Price:USD $75.00
Book Description:

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 fitting techniques used to train...
More Description

Book Details
Pages:214
Detailed Subjects: Mathematics / Probability & Statistics / Regression Analysis
Physical Dimensions (W X L X H):8.19 x 10.31 x 0.75 Inches
Book Weight:1.538 Pounds



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