Multilinear subspace learning is an approach for disentangling the causal factor of data formation and performing dimensionality reduction. The Dimensionality...

tensor Glossary of tensor theory Metric tensor Bra–ket notation Multilinear subspace learning Multivector Geometric algebra Clifford algebra Closed and exact...

Tensor (multilinear) factor analysis disentangles and reduces the influence of different causal factors with multilinear subspace learning. When treating...

representation can be used in dimensionality reduction through multilinear subspace learning. The main linear technique for dimensionality reduction, principal...

Learning automata Learning classifier systems Learning vector quantization Minimum message length (decision trees, decision graphs, etc.) Multilinear...

subspace Invariant subspace Multilinear subspace learning Quotient space (linear algebra) Signal subspace Subspace topology The term linear subspace is...

sparse, meaning that the mathematical model has many zeros. Multilinear subspace learning algorithms aim to learn low-dimensional representations directly...

mixture of experts Bayesian networks Markov random fields Unsupervised: Multilinear principal component analysis (MPCA) Kalman filters Particle filters Gaussian...

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big data include efficient tensor-based computation, such as multilinear subspace learning, massively parallel-processing (MPP) databases, search-based...

associated with a positive definite kernel. In multilinear subspace learning, PCA is generalized to multilinear PCA (MPCA) that extracts features directly...

Grand Tour Linear least squares Model order reduction Multilinear PCA Multilinear subspace learning Principal component analysis Singular value decomposition...

Factor analysis Genetic algorithms Intention mining Learning classifier system Multilinear subspace learning Neural networks Regression analysis Sequence mining...

Exploratory data analysis Fourier analysis Machine learning Multilinear PCA Multilinear subspace learning Multiway data analysis Nearest neighbor search Nonlinear...

Multi-task learning Multilinear subspace learning Multimodal learning Multiple instance learning Multiple-instance learning Never-Ending Language Learning Offline...

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trick for more information). Blind signal separation Multilinear PCA Multilinear subspace learning Nonlinear dimensionality reduction Orthogonal matrix...

Berlin, 2002, 447–460. M.A.O. Vasilescu, D. Terzopoulos (2003) "Multilinear Subspace Analysis for Image Ensembles, M. A. O. Vasilescu, D. Terzopoulos...

multilinear algebra and structured data fusion. Tensor Toolbox Multilinear algebra MATLAB software. MPCA and MPCA+LDA Multilinear subspace learning software:...

transforms Geohash – Public domain geocoding invented in 2008 Multilinear subspace learning – Approach to dimensionality reduction Principal component analysis –...

using the Fisherface algorithm, the hidden Markov model, the multilinear subspace learning using tensor representation, and the neuronal motivated dynamic...

Curvilinear coordinates Tensors in curvilinear coordinates Multilinear subspace learning Multilinear algebra Differential geometry Ricci, Gregorio; Levi-Civita...

Recently, this problem has been answered negatively. Multilinear algebra Multilinear subspace learning Tensor Tensor decomposition Tensor software Suvrit...

analysis Linear discriminant analysis Curse of dimensionality Multilinear subspace learning Cook & Adragni (2009) Sufficient Dimension Reduction and Prediction...

electronic tongue illustrates relevant multiway processing. Multilinear subspace learning Coppi, R.; Bolasco, S., eds. (1989). Multiway Data Analysis...

learning Multilinear subspace learning McKinney, Brett A.; Reif, David M.; Ritchie, Marylyn D.; Moore, Jason H. (1 January 2006). "Machine learning for...

product of modules Tensor product of fields Linearly disjoint Multilinear subspace learning Kassel (1995), p. 32. Lang 2002, pp. 629–630. Kassel (1995)...

vocabulary in the corresponding topic. Latent class analysis Multilinear subspace learning Singular value decomposition Tucker decomposition Higher-order...

Venetsanopoulos and his research team developed a framework of multilinear subspace learning, so that computation and memory demands are reduced, natural...

if and only if all its coefficients are zero. Linear subspace A linear subspace or vector subspace W of a vector space V is a non-empty subset of V that...