Web: http://arxiv.org/abs/2108.04428

May 9, 2022, 1:10 a.m. | Yuefeng Han, Cun-Hui Zhang

stat.ML updates on arXiv.org arxiv.org

The CP decomposition for high dimensional non-orthogonal spiked tensors is an
important problem with broad applications across many disciplines. However,
previous works with theoretical guarantee typically assume restrictive
incoherence conditions on the basis vectors for the CP components. In this
paper, we propose new computationally efficient composite PCA and concurrent
orthogonalization algorithms for tensor CP decomposition with theoretical
guarantees under mild incoherence conditions. The composite PCA applies the
principal component or singular value decompositions twice, first to a matrix
unfolding …

analysis arxiv ml models tensor

More from arxiv.org / stat.ML updates on arXiv.org

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC

Senior Data Science Writer

@ NannyML | Remote

Director of AI/ML Engineering

@ Armis Industries | Remote (US only), St. Louis, California

Digital Analytics Manager

@ Patagonia | Ventura, California