We address the problem of minimizing a convex function over the space of large matrices with low rank. While this optimization problem is hard in general, we propose an efficient...
We investigate techniques for analysis and retrieval of object trajectories in a two or three dimensional space. Such kind of data usually contain a great amount of noise, that ma...
Michail Vlachos, Dimitrios Gunopulos, George Kolli...
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
The availability of high density single nucleotide polymorphisms (SNPs) data has made genome-wide association study computationally challenging. Twolocus epistasis (gene-gene inter...
This paper presents research on the application of the means-end chain (MEC) framework for investigating customers cognitive structure regarding community applications. It is argu...