Abstract: For the low-rank matrix recovery problem, algorithms that directly manipulate the low-rank matrix typically require computing the top singular values/vectors of the matrix and thus are ...
Abstract: Unsupervised learning provides efficient analytical tools for data-centric Internet of Things (IoT) applications. nonnegative matrix factorization (NMF) is a fundamental tool in unsupervised ...
On-device learning has emerged as a promising direction for AI development, particularly because of its potential to reduce latency issues and mitigate privacy risks associated with device-server ...
Reference implementation and reproduction materials for the paper: H. Yan, K. Paynabar, and J. Shi, “Image-based process monitoring using low-rank tensor ...
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