Computational Statistics and Machine Learning : A Sparse Approach (Wiley Series in Probability and Statistics)

Shawe-Taylor, John/ Hussain, Zakria

Wiley-Blackwell（2021/08発売）

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製本 Hardcover:ハードカバー版／ページ数 352 p.
言語 ENG
商品コード 9780470973561
DDC分類 519.50285

Full Description

Computational Statistics and Machine Learning: A Sparse Approach focuses on using sparse algorithms in statistics and machine learning. The first part addresses the L-0 norm minimization using greedy algorithms and considers the set covering machines, matching pursuit algorithms in machine learning, and random projection methods. The second part, which addresses L-1 norm minimization, discusses linear programming boosting, LASSO/LARS, and compressed sensing. All chapters include a detailed description of algorithms and pseudo-code and, where appropriate, a theoretical analysis of generalization ability motivating the use of sparsity. A final chapter covers applications.