Abstract. Linear Discriminant (LD) techniques are typically used in pattern recognition tasks when there are many (n >> 104 ) datapoints in low-dimensional (d < 102 ) spac...
Given a set of n points in d-dimensional Euclidean space, S ⊂ Ed , and a query point q ∈ Ed , we wish to determine the nearest neighbor of q, that is, the point of S whose Euc...
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Abstract A Boolean function is called normal if it is constant on flats of certain dimensions. This property is relevant for the construction and analysis of cryptosystems. This p...
In this paper, an extension of a dimensionality reduction algorithm called NONNEGATIVE MATRIX FACTORIZATION is presented that combines both `bag of words' data and syntactic ...