We present a new visualization of the distance and cluster structure of high dimensional data. It is particularly well suited for analysis tasks of users unfamiliar with complex d...
Constraint satisfaction consistency preprocessing methods are used to reduce search e ort. Time and especially space costs limit the amount of preprocessing that will be cost e ec...
Realistic acoustic modeling is essential for spatializing sound in distributed virtual environments where multiple networked users move around and interact visually and aurally in...
This paper deals with the problem of blind source separation in fMRI data analysis. Our main contribution is to present a maximum likelihood based method to blindly separate the b...
Most manifold learning methods consider only one similarity matrix to induce a low-dimensional manifold embedded in data space. In practice, however, we often use multiple sensors...