Tensor decomposition and applications
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Scope of this subject
This cluster of papers focuses on the theory and applications of tensor decompositions, particularly in the context of multilinear algebra. It covers various decomposition methods such as Singular Value Decomposition, Parallel Factor Analysis, Canonical Polyadic Decomposition, and Tucker Decomposition, along with their applications in signal processing and machine learning.
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Research vocabulary
tensor decomposition; tensor completion; Tucker decomposition; higher-order tensors; tensors; tensor rank; canonical polyadic decomposition; higher-order singular value decomposition; alternating least squares; symmetric tensors; multilinear algebra; low-rank tensor approximation; tensor train decomposition; CP decomposition; low-rank tensor completion; CANDECOMP/PARAFAC; nonnegative tensor factorization; third-order tensors; low-rank tensor decomposition; low-rank tensor; tensor train format; multiway data; low-rank tensor recovery; tensor train; tensor singular value decomposition
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Numeric address and provenance
Morton address: 38351240459119805 · morton4x16-v1
Coordinates: (3, 26, 2605, 12303). The address interleaves categorical identifier bits. Nearby addresses are not guaranteed to describe semantically similar subjects.
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