Nonnegative matrix factorization / Nicolas Gillis

• Autore: Gillis, Nicolas
• Pubblicazione: Philadelphia, : SIAM, 2021
• Descrizione fisica: xix, 350 p. : ill. ; 26 cm
• Soggetto topico: 68-XX - Computer science [MSC 2020]; 15B48 - Positive matrices and their generalizations; cones of matrices [MSC 2020]; 15-XX - Linear and multilinear algebra; matrix theory [MSC 2020]; 68T10 - Pattern recognition, speech recognition [MSC 2020]; 15A23 - Factorization of matrices [MSC 2020]; 68T09 - Computational aspects of data analysis and big data [MSC 2020]; 65F55 - Numerical methods for low-rank matrix approximation; matrix compression [MSC 2020]
• Soggetto non controllato: Computational complexity; Dictionary learning; Gene expression analysis; Hyperspectral Imaging; Matrix Factorization; Non-linear optimization; Nonnegative matrix factorization; Principal component analysis; Recommender systems; Singular value decomposition; Sparsity; audio source separation; beta-divergences; blind source separation; block coordinate descent methods; communication complexity; extended formulations; feature extraction; identifiability; linear dimensionality reduction; low-rank matrix approximations; multiplicative updates; nested polytope problem; nonnegative rank; self-modeling curve resolution; separability; topic modeling
• Titolo autorizzato: Nonnegative matrix factorization
• ISBN: 978-16-11-97640-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: VAN0265397
• Lo trovi qui: Univ. Vanvitelli
• Localizzazioni e accesso elettronico: /sebina/repository/catalogazione/documenti/GILLIS.pdf
• Serie: Data science book series Philadelphia . -SIAM ; 2