Online blind deconvolution for Astronomy (2009)
Harmeling, S., Hirsch, M., Sra, S., Schölkopf, B.
Atmospheric turbulences blur astronomical images taken by earth-based telescopes. Taking many short-time exposures in such a situation provides noisy images of the same object, where each noisy image...
From outliers to prototypes: Ordering data (2006)
Harmeling, S., Dornhege, G., Tax, D., Meinecke, F.
We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show that these...
Inlier-based ICA with an application to superimposed images (2005)
This paper proposes a new independent component analysis (ICA) method which is able to unmix overcomplete mixtures of sparce or structured signals like speech, music or images. Furthermore, the...
VERFAHREN UND VORRICHTUNG ZUM ANALYSIEREN VON BELIEBIGEN OBJEKTEN (2004)
Harmeling, S., Mueller, K., Meinecke, F., Dornhege, G.
WO2004006072 A UPAB: 20040205 NOVELTY - The method involves generating a statistic using pairwise relations for each object, and ordering the objects according to values of the statistics. The order...
Ziehe, A., Kawanabe, M., Harmeling, S.
We propose two methods that reduce the post-nonlinear blind source separation problem (PNL-BSS) to a linear BSS problem. The first method is based on the concept of maximal correlation: we apply the...
Robust ICA for super-gaussian sources (2004)
Most ICA algorithms are sensitive to outliers. Instead of robustifying existing algorithms by outlier rejection techniques, we show how a simple outlier index can be used directly to solve the ICA...
Honkela, A., Harmeling, S., Lundqvist, L., Valpola, H.
The variational Bayesian nonlinear blind source separation method introduced by Lappalainen and Honkela in 2000 is initialised with linear principal component analysis (PCA). Because of the...
Injecting noise for analysing the stability of ICA components (2004)
Harmeling, S., Meinecke, F., Müller, K.R.
Usually, noise is considered to be destructive. We present a new method that constructively injects noise to assess the reliability and the grouping structure of empirical ICA component estimates....
Kernel-based nonlinear blind source separation (2003)
Harmeling, S., Ziehe, A., Kawanabe, M., Mueller, K.R.
We propose kTDSEP, a kernel-based algorithm for nonlinear blind source separation (BSS). It combines complementary research fields: kernel feature spaces and BSS using temporal information. This...
Vorrichtung und Verfahren zur Quellentrennung (2003)
Ziehe, A., Harmeling, S., Mueller, K., Kawanabe, M.
DE 10160519 A UPAB: 20030324 NOVELTY - Device for source separation comprises a source separation unit (24) with inputs for at least two number series representing sequences, time series or vectors....
Verfahren und Vorrichtung zum Entmischen post-nichtlinear gemischter Signale (2003)
Ziehe, A., Harmeling, S., Mueller, K., Kawanabe, M.
DE 10162075 A UPAB: 20030731 NOVELTY - The method involves representing the mixed signal with a series of n-tuples and describing the non-linear part of the post-nonlinear mixing with n...