Over the years, many Linear Discriminant Analysis (LDA) algorithms have been proposed for the study of high dimensional data in a large variety of problems. An intrinsic limitatio...
This paper addresses the inference of probabilistic classification models using weakly supervised learning. In contrast to previous work, the use of proportion-based training data...
Carla Scalarin, Jacques Masse, Jean-Marc Boucher, ...
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
Background: Analysis of complex samples with tandem mass spectrometry (MS/MS) has become routine in proteomic research. However, validation of database search results creates a bo...
One successful approach to feature extraction in face recognition problems is that of linear discriminant analysis (LDA). We examine an extension of this technique, called angular...
Raymond S. Smith, Josef Kittler, Miroslav Hamouz, ...