In this paper we derive an independent-component analysis (ICA) method for analyzing two or more data sets simultaneously. Our model extracts independent components common to all ...
Ana S. Lukic, Miles N. Wernick, Lars Kai Hansen, J...
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
We introduce FuncICA, a new independent component analysis method for pattern discovery in inherently functional data, such as time series data. FuncICA can be considered an analo...
Abstract In this paper, we describe a novel approach to intrinsic plagiarism detection. Each suspicious document is divided into a series of consecutive, potentially overlapping â€...