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Tensor Regression (Paperback)
Loot Price: R2,362
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Tensor Regression (Paperback)
Series: Foundations and Trends (R) in Machine Learning
Expected to ship within 10 - 15 working days
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Regression analysis is a key area of interest in the field of data
analysis and machine learning which is devoted to exploring the
dependencies between variables, often using vectors. The emergence
of high dimensional data in technologies such as neuroimaging,
computer vision, climatology and social networks, has brought
challenges to traditional data representation methods. Tensors, as
high dimensional extensions of vectors, are considered as natural
representations of high dimensional data. In this book, the authors
provide a systematic study and analysis of tensor-based regression
models and their applications in recent years. It groups and
illustrates the existing tensor-based regression methods and covers
the basics, core ideas, and theoretical characteristics of most
tensor-based regression methods. In addition, readers can learn how
to use existing tensor-based regression methods to solve specific
regression tasks with multiway data, what datasets can be selected,
and what software packages are available to start related work as
soon as possible. Tensor Regression is the first thorough overview
of the fundamentals, motivations, popular algorithms, strategies
for efficient implementation, related applications, available
datasets, and software resources for tensor-based regression
analysis. It is essential reading for all students, researchers and
practitioners of working on high dimensional data.
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