K
Klaus-Robert Müller
Researcher at Technical University of Berlin
Publications - 799
Citations - 98394
Klaus-Robert Müller is an academic researcher from Technical University of Berlin. The author has contributed to research in topics: Artificial neural network & Computer science. The author has an hindex of 129, co-authored 764 publications receiving 79391 citations. Previous affiliations of Klaus-Robert Müller include Korea University & University of Tokyo.
Papers
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Objective quality assessment of stereoscopic images with vertical disparity using EEG.
Forooz Shahbazi Avarvand,Sebastian Bosse,Klaus-Robert Müller,Klaus-Robert Müller,Ralf Schäfer,Guido Nolte,Thomas Wiegand,Thomas Wiegand,Gabriel Curio,Wojciech Samek +9 more
TL;DR: The results suggest that the vertical disparity in 3D-3 condition decreases the perception of depth compared to other 3D conditions and the amplitude of P1 component can be used as a discriminative feature.
Nonparametric Density Estimation for Human Pose Tracking
Thomas Brox,Bodo Rosenhahn,Uwe G. Kersting,Daniel Cremers,Katrin Franke,Klaus-Robert Müller,Bertram Nickolay,Ralf Schäfer +7 more
TL;DR: In this paper, the supplement of prior knowledge about joint angle configurations in the scope of 3D human pose tracking is considered for a nonparametric Parzen density estimation in the 12-dimensional joint configuration space.
Generalization Error Estimation under Covariate Shift
TL;DR: This paper proposes an alternative estimator of the generalization error which is under the covariate shift exactly unbiased if model includes the learning target function and is asymptotically unbiased in general and shows that the proposed method compares favorably with cross-validation.
Journal ArticleDOI
Distributed functions of detection and discrimination of vibrotactile stimuli in the hierarchical human somatosensory system.
Junsuk Kim,Klaus-Robert Müller,Yoon Gi Chung,Soon Cheol Chung,Jang-Yeon Park,Heinrich H. Bülthoff,Heinrich H. Bülthoff,Sung-Phil Kim +7 more
TL;DR: The results showed that vibrotactile stimulus locations on fingers could be discriminated from measurements of human functional magnetic resonance imaging (fMRI), and supported the general understanding that S1 is the main sensory receptive area for the sense of touch, and adjacent cortical regions are in charge of a higher level of processing and may contribute most for the successful classification between stimulated finger locations.
Journal ArticleDOI
Trading variance reduction with unbiasedness: the regularized subspace information criterion for robust model selection in kernel regression
TL;DR: This article derives an unbiased estimator of the expected squared error, between SIC and the expected generalization error and proposes determining the degree of regularization of SIC such that the estimators of theexpected squared error is minimized.