We present the Iterated-Tverberg algorithm, the first deterministic algorithm for computing an approximate centerpoint of a set S ∈ Rd with running time sub-exponential in d. T...
Narrowing-driven partial evaluation is a powerful technique for the specialization of (first-order) functional and functional logic programs. However, although it gives good resu...
A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system ...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...