Cross-validation based Nonlinear Shrinkage

no code implementations • 2 Nov 2016 • Daniel Bartz

Many machine learning algorithms require precise estimates of covariance matrices.

Validity of time reversal for testing Granger causality

no code implementations • 25 Sep 2015 • Irene Winkler, Danny Panknin, Daniel Bartz, Klaus-Robert Müller, Stefan Haufe

Inferring causal interactions from observed data is a challenging problem, especially in the presence of measurement noise.

valid

Multi-Target Shrinkage

no code implementations • 5 Dec 2014 • Daniel Bartz, Johannes Höhne, Klaus-Robert Müller

For the sample mean and the sample covariance as specific instances, we derive conditions under which the optimality of MTS is applicable.

Covariance shrinkage for autocorrelated data

no code implementations • NeurIPS 2014 • Daniel Bartz, Klaus-Robert Müller

data.

EEG Time Series +1

Generalizing Analytic Shrinkage for Arbitrary Covariance Structures

no code implementations • NeurIPS 2013 • Daniel Bartz, Klaus-Robert Müller

Analytic shrinkage is a statistical technique that offers a fast alternative to cross-validation for the regularization of covariance matrices and has appealing consistency properties.

Optical Character Recognition Optical Character Recognition (OCR)