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001 https://directory.doabooks.org/handle/20.500.12854/44618
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020 _a9783038975915
024 _a10.3390/books978-3-03897-591-5
042 _adc
245 0 _aDecomposability of Tensors
260 _bMDPI - Multidisciplinary Digital Publishing Institute
_c2019
300 _a1 electronic resource (160 p.)
520 _aTensor decomposition is a relevant topic, both for theoretical and applied mathematics, due to its interdisciplinary nature, which ranges from multilinear algebra and algebraic geometry to numerical analysis, algebraic statistics, quantum physics, signal processing, artificial intelligence, etc. The starting point behind the study of a decomposition relies on the idea that knowledge of elementary components of a tensor is fundamental to implement procedures that are able to understand and efficiently handle the information that a tensor encodes. Recent advances were obtained with a systematic application of geometric methods: secant varieties, symmetries of special decompositions, and an analysis of the geometry of finite sets. Thanks to new applications of theoretic results, criteria for understanding when a given decomposition is minimal or unique have been introduced or significantly improved. New types of decompositions, whose elementary blocks can be chosen in a range of different possible models (e.g., Chow decompositions or mixed decompositions), are now systematically studied and produce deeper insights into this topic. The aim of this Special Issue is to collect papers that illustrate some directions in which recent researches move, as well as to provide a wide overview of several new approaches to the problem of tensor decomposition.
540 _aCreative Commons
653 _aborder rank and typical rank
700 1 _aLuca Chiantini
_eeditor
856 _uhttps://docs.google.com/spreadsheets/d/1yKIrdCPDAG_9c22mwoOIO2DOhtj65Wqa/edit?usp=sharing&ouid=106555315294820607512&rtpof=true&sd=true
_yList of Curated E-Books
942 _cE-BOOK
999 _c46248
_d46248