Matrix Factorization

SVD (Singular Value Decomposition)

Fundamental method decomposing any matrix M into the product UΣVᵀ where U and V are orthogonal and Σ is diagonal with singular values. Provides the best rank-k approximation in the least squares sense and reveals the intrinsic structure of the data.

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