Parallel algorithms for singular value decomposition (SVD) have risen to prominence as an indispensable tool in high-performance numerical linear algebra. They offer significant improvements in the ...
Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...
Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...
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