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portada Generalized Low Rank Models (in English)
Type
Physical Book
Author
Publisher
Language
Inglés
Pages
142
Format
Paperback
Dimensions
23.4 x 15.6 x 0.8 cm
Weight
0.21 kg.
ISBN13
9781680831405
Categories

Generalized Low Rank Models (in English)

Madeleine Udell (Author) · Corinne Horn (Author) · Reza Zadeh (Author) · Now Publishers · Paperback

Generalized Low Rank Models (in English) - Udell, Madeleine ; Horn, Corinne ; Zadeh, Reza

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Synopsis "Generalized Low Rank Models (in English)"

Principal components analysis (PCA) is a well-known technique for approximating a tabular data set by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets consisting of numerical, Boolean, categorical, ordinal, and other data types. This framework encompasses many well-known techniques in data analysis, such as nonnegative matrix factorization, matrix completion, sparse and robust PCA, k-means, k-SVD, and maximum margin matrix factorization. The method handles heterogeneous data sets, and leads to coherent schemes for compressing, denoising, and imputing missing entries across all data types simultaneously. It also admits a number of interesting interpretations of the low rank factors, which allow clustering of examples or of features. We propose several parallel algorithms for fitting generalized low rank models, and describe implementations and numerical results.

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