Increasingly large amount of multidimensional data are being generated on a daily basis in
many applications. This leads to a strong demand for learning algorithms to extract useful …

Tensor (multiway array) factorization and decomposition has become an important tool for
data mining. Fueled by the computational power of modern computer researchers can now …

This survey provides an overview of higher-order tensor decompositions, their applications,
and available software. A tensor is a multidimensional or-way array. Decompositions of …

This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix
Factorization (NMF). This includes NMF's various extensions and modifications, especially …

Nowadays, there are two significant tendencies, how to process the enormous amount of
data, big data, and how to deal with the green issues related to sustainability and …

Research in tensor representation and analysis has been rising in popularity in direct
response to a) the increased ability of data collection systems to store huge volumes of …

This paper introduces a multilinear principal component analysis (MPCA) framework for
tensor object feature extraction. Objects of interest in many computer vision and pattern …

In this paper we introduce a new class of tensor decompositions. Intuitively, we decompose
a given tensor block into blocks of smaller size, where the size is characterized by a set of …

We present an alternative strategy for truncating the higher-order singular value
decomposition (T-HOSVD). An error expression for an approximate Tucker decomposition …

Feature extraction and selection are key factors in model reduction, classification and
pattern recognition problems. This is especially important for input data with large …