Structured representation learning from complex data


Autoria(s): Nguygen, Tu Dinh
Contribuinte(s)

Phung, Dinh

Venkatesh, Svetha

Tran, Truyen

Data(s)

01/04/2015

Resumo

This thesis advances several theoretical and practical aspects of the recently introduced restricted Boltzmann machine - a powerful probabilistic and generative framework for modelling data and learning representations. The contributions of this study represent a systematic and common theme in learning structured representations from complex data.

Identificador

http://hdl.handle.net/10536/DRO/DU:30079713

Idioma(s)

eng

Publicador

Deakin Univeristy, Faculty of Science Engineering and Built Environment, School of Information Technology

Relação

http://dro.deakin.edu.au/eserv/DU:30079713/nguyen-agreement-2015.pdf

http://dro.deakin.edu.au/eserv/DU:30079713/nguyen-structuredrepresentation-2015A.pdf

Direitos

The Author. All Rights Reserved

Palavras-Chave #statistical machine learning #annotated labels #restricted Boltzmann machine #structured representations
Tipo

Thesis