We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
We propose a range of deep lexical acquisition methods which make use of morphological, syntactic and ontological language resources to model word similarity and bootstrap from a ...
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
: Dynamic Web data sources – sometimes known collectively as the Deep Web – increase the utility of the Web by providing intuitive access to data repositories anywhere that Web...
Daniel Rocco, James Caverlee, Ling Liu, Terence Cr...
Cache memories account for a significant fraction of a chip's overall energy dissipation. Recent research advocates using "resizable" caches to exploit cache requir...
Se-Hyun Yang, Michael D. Powell, Babak Falsafi, T....