We propose randomized techniques for speeding up Kernel Principal Component Analysis on three levels: sampling and quantization of the Gram matrix in training, randomized rounding...
Dimitris Achlioptas, Frank McSherry, Bernhard Sch&...
We describe methods for the specification and modification of virtual resections in medical volume data. These techniques are focused on applications in therapy planning, but are a...
Starting from a model of the within-die systematic variations using principal components analysis, a model is proposed for estimation of the parametric yield, and is then applied ...
This study explores the feasibility of estimating the Body Condition Score (BCS) of cows from digital images by employing statistical shape analysis and regression machines. The s...
Sebastiano Battiato, Giovanni Maria Farinella, Giu...
In this paper, it is shown that Independent Component Analysis (ICA) of sparse signals (sparse ICA) can be seen as a cluster-wise Principal Component Analysis (PCA). Consequently,...
Massoud Babaie-Zadeh, Christian Jutten, Ali Mansou...