Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
Motivated by the growing interest in the use of ridges in scientific visualization, we analyze the two height ridge definitions by Eberly and Lindeberg. We propose a raw feature d...
We present the Zoomable Adjacency Matrix Explorer (ZAME), a visualization tool for exploring graphs at a scale of millions of nodes and edges. ZAME is based on an adjacency matrix...
Niklas Elmqvist, Thanh-Nghi Do, Howard Goodell, Na...
We present a novel classification technique for volume visualization that takes the shape of volumetric features into account. The presented technique enables the user to distingu...
In this paper, we introduce a new method, GraphScape, to visualize multivariate networks, i.e., graphs with multivariate data associated with their nodes. GraphScape adopts a land...
Kai Xu 0003, Andrew Cunningham, Seok-Hee Hong, Bru...