Relational discriminant analysis is based on a proximity description of the data. Instead of features, the similarities to a subset of the objects in the training data are used for representation. In this paper we will show that this subset might be small and that its exact choice is of minor importance. Moreover, it is shown that linear or non-linear methods for feature extraction based on mul...

CCA can be seen as a multiview extension of PCA, in which information from two sources is used for learning by finding a subspace in which the two views are most correlated. However PCA, and by extension CCA, does not use label information. Fisher Discriminant Analysis uses label information to find informative projections, which can be more informative in supervised learning settings. We show ...

In this paper, we show the existence of a non-solvable Galois extension of Q which is unramified outside 2. The extension K we construct has degree 2251731094732800 = 2(3 · 5 · 17 · 257) and has root discriminant δK < 2 47 8 = 58.68..., and is totally complex.

Re-identification of individuals across camera networks with limited or no overlapping fields of view remains challenging in spite of significant research efforts. In this paper, we propose the use, and extensively evaluate the performance, of four alternatives for re-ID classification: regularized Pairwise Constrained Component Analysis, kernel Local Fisher Discriminant Analysis, Marginal Fish...

This paper presents a constructive method for deriving an updated discriminant eigenspace for classification, when bursts of new classes of data is being added to an initial discriminant eigenspace in the form of random chunks. The proposed Chunk incremental linear discriminant analysis (I-LDA) can effectively evolve a discriminant eigenspace over a fast and large data stream, and extract featu...

B on an extensive survey conducted on the representative sample of displaced persons from Croatian East the purpose of this paper was to highlight the differences in some sociodemographic characteristics, attitudes and expectations of the displaced who distinguish by their willingness to return home under the conditions of the Plan of Peaceful Reintegration. The majority (about 70%) of the inte...

In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application. In this framework, the benefits of dimensionality reduction were used to improve the performance of its predictive model, which was a support vector machine (...