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Wiley Interdisciplinary Reviews: Computational Statistics, ISSN 1939-5108, 07/2010, Volume 2, Issue 4, pp. 433 - 459
Journal Article
Nature Physics, ISSN 1745-2473, 2014, Volume 10, Issue 9, pp. 631 - 633
The usual way to reveal properties of an unknown quantum state, given many copies of a system in that state, is to perform measurements of different... 
PHYSICS, MULTIDISCIPLINARY | MATRICES | ALGORITHMS | Principal components analysis | Quantum physics | Algorithms | Eigenvalues | Tomography | Data processing | Eigenvectors | Transformations | Density | Principal component analysis | Physics - Quantum Physics
Journal Article
Journal of Computational and Graphical Statistics, ISSN 1061-8600, 06/2006, Volume 15, Issue 2, pp. 265 - 286
Journal Article
2002, 2nd ed., Springer series in statistics., ISBN 0387954422, xxix, 487
Book
Nature Biotechnology, ISSN 1087-0156, 03/2008, Volume 26, Issue 3, pp. 303 - 304
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 12/2011, Volume 20, Issue 12, pp. 3419 - 3430
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 10/2019, Volume 41, Issue 10, pp. 2365 - 2379
Dictionary learning and component analysis models are fundamental for learning compact representations that are relevant to a given task (feature extraction,... 
Dictionaries | Computational modeling | sparsity | dictionary learning | global optimality | Sparse matrices | Tensile stress | Machine learning | low-rank | Component analysis | Data models | separable dictionaries | Principal component analysis | Low-rank | Global Optimality | Dictionary Learning | Sparsity | Component Analysis | Separable Dictionaries
Journal Article
Pattern Recognition, ISSN 0031-3203, 06/2018, Volume 78, pp. 215 - 227
When modeling multivariate data, one might have an extra parameter of contextual information that could be used to treat some observations as more similar to... 
Manifold approximation | Face modeling | Manifold learning | Principal component analysis | ACTIVE APPEARANCE MODELS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer Science - Computer Vision and Pattern Recognition
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