Network embedding theories, methods, and applications

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Yang, Cheng (VerfasserIn), Liu, Zhiyuan (VerfasserIn), Tu, Cunchao (VerfasserIn), Shi, Chuan (VerfasserIn), Sun, Maosong (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	[San Rafael, California] Morgan & Claypool Publishers [2021]
Schriftenreihe:	Synthesis lectures on artificial intelligence and machine learning #48
Schlagworte:	Machine learning Neural networks (Computer science) Vector spaces
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