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Sparse Modeling

Sparse Modeling

Theory, Algorithms, and Applications

by Irina Rish and Genady Grabarnik
Hardback
Publication Date: 01/12/2014

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Sparse modeling is an important issue in many applications of machine learning and statistics where the main objective is discovering predictive patterns in data to enhance understanding of underlying physical, biological, and other natural processes. This book surveys recent advances in statistics, machine learning, and signal processing related to sparse modeling. It provides a comprehensive introduction to recent developments in sparse modeling research, including the theoretical basis for sparse modeling, algorithmic approaches, and applications to computational biology, medicine, neuroscience, graphical model selection, and compressed sensing.
ISBN:
9781439828694
9781439828694
Category:
Machine learning
Format:
Hardback
Publication Date:
01-12-2014
Language:
English
Publisher:
Taylor & Francis Inc
Country of origin:
United States
Pages:
254
Dimensions (mm):
234x156x18mm
Weight:
0.8kg

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