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Can I read Advances in Independent Component Analysis and Learning Machines on EtoBox?

Advances in Independent Component Analysis and Learning Machines by Ella Bingham; Samuel Kaski; Jorma Laaksonen; Jouko Lampinen; Erkki Oja is a nonfiction available to read on EtoBox.

What is Advances in Independent Component Analysis and Learning Machines about?

In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithm Unsupervised deep learning Machine vision and image retrieval A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning. A diverse set of application fields, ranging from machine vision to science policy data. Contributions from leading researchers in the field.

Who reads Advances in Independent Component Analysis and Learning Machines?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Ella Bingham; Samuel Kaski; Jorma Laaksonen; Jouko Lampinen; Erkki Oja
Publisher
Elsevier Science & Technology Books; Academic Press
Published
2015
Language
EN
ISBN
9780128028063
Category
nonfiction
Subjects
Engineering, Mathematics, Technology

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