iPhoneAlle anzeigen
iPhone 11iPhone 11 ProiPhone 11 Pro MaxiPhone 12iPhone 12 ProiPhone 12 Pro MaxiPhone 12 miniiPhone 13iPhone 13 ProiPhone 13 Pro MaxiPhone 13 miniiPhone 14iPhone 14 PlusiPhone 14 ProiPhone 14 Pro MaxiPhone 15iPhone 15 PlusiPhone 15 ProiPhone 15 Pro MaxiPhone 16iPhone 16 PlusiPhone 16 ProiPhone 16 Pro MaxiPhone 16eiPhone 5iPhone 5CiPhone 5SiPhone 6iPhone 6 PlusiPhone 6SiPhone 6S PlusiPhone 7iPhone 7 PlusiPhone 8iPhone 8 PlusiPhone SEiPhone SE 2020iPhone SE 2022iPhone XiPhone XRiPhone XSiPhone XS Max
NokiaAlle anzeigen
108 Reihe220 Reihe225 Reihe2600 classic Reihe2680 slide Reihe2710 Reihe3120 classic Reihe3220 Reihe500 Reihe515 Reihe5230 Reihe603 Reihe6131 Reihe6200 Reihe6300 Reihe6500 Reihe6700 Reihe700 Reihe7200 Reihe8310 ReiheAshaC1C2C3C5C6C7E51E52E6E63E65E7E71E72N73N8N9N95N97Nokia 3Nokia 4.2Nokia 5Nokia 6Nokia 7Nokia 8SiroccoWeitere ModelleXX2X3X6XLXpressMusic
Galaxy A-SerieAlle anzeigen
Galaxy A12Galaxy A13Galaxy A13 5GGalaxy A14Galaxy A15Galaxy A16Galaxy A17Galaxy A17 5GGalaxy A20eGalaxy A21Galaxy A22Galaxy A23Galaxy A24Galaxy A25Galaxy A26 5GGalaxy A27 5GGalaxy A3Galaxy A32Galaxy A33Galaxy A34Galaxy A35Galaxy A36 5GGalaxy A37Galaxy A40Galaxy A41Galaxy A42Galaxy A50Galaxy A51Galaxy A52Galaxy A53Galaxy A54Galaxy A55Galaxy A56 5GGalaxy A57 5GGalaxy A70Galaxy A71Galaxy A72
Redmi SeriesAlle anzeigen
Redmi 10Redmi 13CRedmi 15 5GRedmi Note 10Redmi Note 10 ProRedmi Note 11Redmi Note 11 ProRedmi Note 11 Pro Plus 5GRedmi Note 11sRedmi Note 12Redmi Note 12 5GRedmi Note 12 ProRedmi Note 12 Pro 5GRedmi Note 12 Pro PlusRedmi Note 13Redmi Note 13 5GRedmi Note 13 ProRedmi Note 13 Pro PlusRedmi Note 14Redmi Note 14 Pro PlusRedmi Note 15Redmi Note 15 5GRedmi Note 15 ProRedmi Note 15 Pro 5GRedmi Note 15 Pro Plus 5GRedmi Note 8Redmi Note 8 ProRedmi Note 9Redmi Note 9 Pro
- Startseite
Bücher Wissen & Bildung Englische Bücher Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Robust Latent Feature Learning for Incomplete Big Data
Handgeprüfte Gebrauchtware
Bis zu 50 % günstiger als neu
Der Umwelt zuliebe
Optischer Zustand
Beschreibung
Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature analysis (LFA) is one of the most popular representation learning methods tailored for incomplete… big data due to its high accuracy, computational efficiency, and ease of scalability. The crux of analyzing incomplete big data lies in addressing the uncertainty problem caused by their incomplete characteristics. However, existing LFA methods do not fully consider such uncertainty. In this book, the author introduces several robust latent feature learning methods to address such uncertainty for effectively and efficiently analyzing incomplete big data, including robust latent feature learning based on smooth L 1 -norm, improving robustness of latent feature learningusing L 1 -norm, improving robustness of latent feature learning using double-space, data-characteristic-aware latent feature learning, posterior-neighborhood-regularized latent feature learning, and generalized deep latent feature learning. Readers can obtain an overview of the challenges of analyzing incomplete big data and how to employ latent feature learning to build a robust model to analyze incomplete big data. In addition, this book provides several algorithms and real application cases, which can help students, researchers, and professionals easily build their models to analyze incomplete big data. 53,49 €
Broschiert | Neu
oder
zzgl.
Du kannst wie immer einen Kaufalarm setzen, wenn du auf das gebrauchte Buch warten möchtest.
zzgl.
Handgeprüfte Gebrauchtware
Bis zu 50 % günstiger als neu
Der Umwelt zuliebe
Technische Daten
Erscheinungsdatum
08.12.2022
Sprache
Englisch
EAN
9789811981395
Herausgeber
Springer Singapore
Serien- oder Bandtitel
SpringerBriefs in Computer Science
Sonderedition
Nein
Autor
Di Wu
Seitenanzahl
112
Einbandart
Broschiert
Schlagwörter
Latent feature learning, Representation learning, Robustness, Incomplete big data, Incomplete matrix, Missing data estimation
Thema-Inhalt
UN - Datenbanken
UNF - Data Mining
UYQE - Wissensbasierte Systeme, Expertensysteme
Höhe
235 mm
Breite
15.5 cm
Transparenz & Sicherheit
Hersteller: Springer, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
-.-
★★★★★
☆☆☆☆☆ Leider noch keine Bewertungen
Leider noch keine Bewertungen
Sicher bei rebuy kaufen
Schreib die erste Bewertung für dieses Produkt!
Wenn du eine Bewertung für dieses Produkt schreibst, hilfst du allen Kund:innen, die noch überlegen, ob sie das Produkt kaufen wollen. Vielen Dank, dass du mitmachst!
Sicher bei rebuy kaufen