Software evolution visualization is a promising technique for assessing the software development process. We study how complex correlations of software evolution attributes can be...
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
We propose a method based on sparse representation
(SR) to cluster data drawn from multiple low-dimensional
linear or affine subspaces embedded in a high-dimensional
space. Our ...
High dimensional directional data is becoming increasingly important in contemporary applications such as analysis of text and gene-expression data. A natural model for multivaria...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
Shape clustering can significantly facilitate the automatic labeling of objects present in image collections. For example, it could outline the existing groups of pathological ce...