Abstract: Abrupt shifts in the level of a time series represent important information and should be preserved in statistical signal extraction. We investigate rules for detecting l...
The majority of theoretical work in machine learning is done under the assumption of exchangeability: essentially, it is assumed that the examples are generated from the same prob...
Vladimir Vovk, Ilia Nouretdinov, Alexander Gammerm...
A general test statistic for detecting change-points in multidimensional stochastic processes with unknown parameters is proposed. The test statistic is specialized to the case of...
Background: The size and magnitude of the metabolome, the ratio between individual metabolites and the response of metabolic networks is controlled by multiple cellular factors. A...
Frank Kose, Jan Budczies, Matthias Holschneider, O...
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...