Existing methods for time series clustering rely on the actual data values can become impractical since the methods do not easily handle dataset with high dimensionality, missing v...
In several contexts and domains, hierarchical agglomerative clustering (HAC) offers best-quality results, but at the price of a high complexity which reduces the size of datasets ...
We consider the problem of determining whether a given set S in Rn is approximately convex, i.e., if there is a convex set K ∈ Rn such that the volume of their symmetric differe...
High-resolution spectroscopy is a powerful industrial tool. The number of features (wavelengths) in these data sets varies from several hundreds up to a thousand. Relevant feature ...
Abstract. In this paper, an efficient speaker identification based on robust vector quantization principal component analysis (VQ-PCA) is proposed to solve the problems from outlie...