On the Information Theoretic Distance Measures and Bidirectional Helmholtz Machines

Autor:	Azarafrooz, Mahdi, Zhao, Xuan, Akhavan-Masouleh, Sepehr
Rok vydání:	2018
Předmět:	Computer Science - Machine Learning Computer Science - Information Theory Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	By establishing a connection between bi-directional Helmholtz machines and information theory, we propose a generalized Helmholtz machine. Theoretical and experimental results show that given \textit{shallow} architectures, the generalized model outperforms the previous ones substantially.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1807.06054 Zobrazit plný text záznamu View this record from Arxiv