Self-similarity was recently introduced as a measure of inter-class congruence for classification of actions. Herein, we investigate the dual problem of intra-class dissimilarity for classification of action styles. We introduce self-dissimilarity matrices that discriminate between same actions performed by different subjects regardless of viewing direction and camera parameters. We investigate...

We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and compare it against several competing techniques: generalized Fisher discriminant analysis (GDA) and kernel principal components analysis (KPCA) in classification problems. We evaluate the classification performance of the ...

A general perspective is provided on both on hypothesis testing and discriminative analyses, by which matrix-variate discriminative analyses are proposed based on the matrix normal distribution, featured by a bi-linear extension of Fisher linear discriminant analysis and a further extension to binary variables. Moreover, a general formulation is proposed for integrative hypothesis testing and f...

The current discriminant analysis method design is generally independent of classifiers, thus the connection between discriminant analysis methods and classifiers is loose. This paper provides a way to design discriminant analysis methods that are bound with classifiers. We begin with a local mean based nearest neighbor (LM-NN) classifier and use its decision rule to supervise the design of a d...

In today’s world, the web has dramatically changed the way that people express their opinions. People use the internet to express their opinion, attitude, feeling and emotion about films, goods, news etc. It is challenging to automatically classify mass subjectivity comments into different sentiment orientation categories (e.g. positive/negative). Furthermore, the ambiguity and randomness, whic...

global warming and predictions of climatic changes additionally put breeding for drought tolerance in the focus of breeding programmes for maize. extensive studies on the existing gene bank collection of the maize research institute “zemun polje“ have been performed with the aim to identify and form initial sources for the development of maize inbreds more tolerant to drought. all accessions (a...

In this paper, a relationship between Linear Discriminant Analysis (LDA) and the generalized Minimum Squared Error (MSE) solution is presented. The generalized MSE solution is shown to be equivalent to applying a certain classification rule in the space defined by LDA. The relationship between the MSE solution and Fisher Discriminant Analysis (FDA) is extended to multi-class problems and also t...

| This review provides an introduction to Support Vector Machines, Kernel Fisher Discriminant analysis and Kernel PCA, as examples for successful kernel based learning methods. We rst give a short background about VC theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrat...

In this paper, a relationship between linear discriminant analysis (LDA) and the generalized minimum squared error (MSE) solution is presented. The generalized MSE solution is shown to be equivalent to applying a certain classification rule in the space defined by LDA. The relationship between the MSE solution and Fisher discriminant analysis is extended to multiclass problems and also to under...