Learning Generative Models for Density Estimation and Function Approximation

博士 === 國立東華大學 === 應用數學系 === 93 === This thesis systematically explores generative models for unsupervised and supervised pattern analysis. By designing and fitting the proposed generative models for unsupervised and supervised pattern analysis, we devise new approaches to solving complex tasks in th...

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Bibliographic Details
Main Authors: Zheng-Han Lin, 林政漢
Other Authors: Jiann-Ming Wu
Format: Others
Language:en_US
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/26599859445399880913