Abstract. Sensor networks represent a non traditional source of information, as readings generated by sensors flow continuously, leading to an infinite stream of data. Traditiona...
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
Many real world data are sampled functions. As shown by Functional Data Analysis (FDA) methods, spectra, time series, images, gesture recognition data, etc. can be processed more e...
In recent years, considerable advances have been made in the study of properties of metric spaces in terms of their doubling dimension. This line of research has not only enhanced...
Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum...
Rex A. Kerr, Thomas M. Bartol, Boris Kaminsky, Mar...