Log-Linear Models, Extensions, and Applications

Author:   Aleksandr Aravkin ,  Anna Choromanska ,  Li Deng ,  Georg Heigold
Publisher:   MIT Press Ltd
ISBN:  

9780262553469


Pages:   214
Publication Date:   03 December 2024
Format:   Paperback
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

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Log-Linear Models, Extensions, and Applications


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Overview

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 models. This volume covers recent advances in training models with log-linear structures, covering the underlying geometry, optimization techniques, and multiple applications. The first chapter shows readers the inner workings of machine learning, providing insights into the geometry of log-linear and neural net models. The other chapters range from introductory material to optimization techniques to involved use cases. The book, which grew out of a NIPS workshop, is suitable for graduate students doing research in machine learning, in particular deep learning, variable selection, and applications to speech recognition. The contributors come from academia and industry, allowing readers to view the field from both perspectives. Contributors Aleksandr Aravkin, Avishy Carmi, Guillermo A. Cecchi, Anna Choromanska, Li Deng, Xinwei Deng, Jean Honorio, Tony Jebara, Huijing Jiang, Dimitri Kanevsky, Brian Kingsbury, Fabrice Lambert, Aurélie C. Lozano, Daniel Moskovich, Yuriy S. Polyakov, Bhuvana Ramabhadran, Irina Rish, Dimitris Samaras, Tara N. Sainath, Hagen Soltau, Serge F. Timashev, Ewout van den Berg

Full Product Details

Author:   Aleksandr Aravkin ,  Anna Choromanska ,  Li Deng ,  Georg Heigold
Publisher:   MIT Press Ltd
Imprint:   MIT Press
Weight:   0.369kg
ISBN:  

9780262553469


ISBN 10:   0262553465
Pages:   214
Publication Date:   03 December 2024
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

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Aleksandr Aravkin is Assistant Professor of Applied Mathematics at the University of Washington. Anna Choromanska is Assistant Professor at New York University's Tandon School of Engineering. Li Deng is Chief Artificial Intelligence Officer of Citadel. Georg Heigold is Research Scientist at Google. Tony Jebara is Associate Professor of Computer Science at Columbia University. Dimitri Kanevsky is Research Scientist at Google. Stephen J. Wright is Professor of Computer Science at the University of Wisconsin–Madison.

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