Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
In this paper, we compare two different approaches for semiautomatic detection of skin hyper-pigmentation on multispectral images. These two methods are support vector machine (SV...
Abstract. Given an LLL-basis B of dimension n = hk we accelerate slide-reduction with blocksize k to run under a reasonable assumption within 1 6 n2 h log1+ε α local SVP-computat...
We show that finding small solutions to random modular linear equations is at least as hard as approximating several lattice problems in the worst case within a factor almost line...