Linear and affine subspaces are commonly used to describe appearance of objects under different lighting, viewpoint, articulation, and identity. A natural problem arising from the...
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...
In this paper we analyze the behavior of quantum random walks. In particular we present several new results for the absorption probabilities in systems with both one and two absor...
Andris Ambainis, Eric Bach, Ashwin Nayak, Ashvin V...
Managing large-scale time series databases has attracted significant attention in the database community recently. Related fundamental problems such as dimensionality reduction, tr...
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...