Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
Threshold agent networks (TANs) constitute a discretized modification of threshold (also known as neural) networks that are appropriate for modeling computer simulations. In this p...
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
Unsupervised over-segmentation of an image into superpixels
is a common preprocessing step for image parsing
algorithms. Superpixels are used as both regions of support
for feat...
Alastair P. Moore, Simon J. D. Prince, Jonathan Wa...
The paper addresses the problem of improving the MPEG compression of synthetic video sequences by exploiting the knowledge about the original 3D model. Two techniques are proposed...