We study the problem of image denoising where images are assumed to be samples from low dimensional (sub)manifolds. We propose the algorithm of locally linear denoising. The algor...
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...
Reliable estimation of the classification performance of learned predictive models is difficult, when working in the small sample setting. When dealing with biological data it is ...
Antti Airola, Tapio Pahikkala, Willem Waegeman, Be...
Abstract--Estimation of the DNA copy number in a given biological sample is an important problem in genomics. Quantitative polymerase chain reaction (qPCR) systems detect the targe...
In this paper, we present a new independent component analysis mixture vector quantization (ICAMVQ) method to summarize the video content. In particular, independent component ana...