In any real-life identification problem, only a finite number of data points is available. On the other hand, almost all results in stochastic identification pertain to asymptotic...
: In this study, we introduce a set of one-dimensional features to represent two dimensional shape information for HMM (Hidden Markov Model) based handwritten optical character rec...
Abstract. We consider column sufficient linear complementarity problems and study the problem of identifying those variables that are zero at a solution. To this end we propose a n...
Francisco Facchinei, Andreas Fischer, Christian Ka...
During a project examining the use of machine learning techniques for oil spill detection, we have encountered several essential questions that we believe deserve the attention of ...
We present the theory for heteroscedastic discriminant analysis (HDA), a model-based generalization of linear discriminant analysis (LDA) derived in the maximum-likelihood framewo...