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 present a software tool for creating an optimal classhierarchy from the use-relationship among data-items and functions based on the method in Kundu and Gwee [3]. The tool dete...
We present a neural-network-based statistical parser, trained and tested on the Penn Treebank. The neural network is used to estimate the parameters of a generative model of left-...
This paper focuses on a novel framework for information retrieval of images based only on color information. Regions homogeneous in color of the input image are detected using a m...
In this paper, we will introduce two different three dimensional VR-based user interface for telecommunication network management. The first one is an immersive system, using HMD ...