We describe deep exponential families (DEFs), a class of latent variable models that are
inspired by the hidden structures used in deep neural networks. DEFs capture a hierarchy of …

Abstract In their article" Deep Exponential Families", Ranganath, Tang, Charlin and Blei
(2014) introduce deep exponential families (DEFs), a special type of hierarchical models …

We describe\textit {deep exponential families}(DEFs), a class of latent variable models that
are inspired by the hidden structures used in deep neural networks. DEFs capture a …

A Generative Model is a powerful way of learning any kind of data distribution using
unsupervised learning. All generative models represent probability distributions over …

Latent variable models are crucial in scientific research, where a key variable, such as effort,
ability, and belief, is unobserved in the sample but needs to be identified. This paper …

We have facing a new Information Technology paradigm called “Big Data”. Social
networking services are strongly related with the Big Data issues. As we have various types …

Since so many marketing studies reflect differing aspects of consumer behavior, there is
today a critical need for data fusion. But fusion can be challenging, especially when we are …

In the recent years, the collection of more and more data instances, has increasingly storing,
managing and collecting of large-scale or diverse data, the research interest of the scientific …

In the recent years, the collection of more and more data instances, has increasingly led to
an abundance. After the investigation of efficient ways to deal with storing, managing and …