PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Nicole Krämer

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Number of EPrints submitted by this user: 19

An Overview on the Shrinkage Properties of Partial Least Squares Regression
Nicole Krämer
Computational Statistics Volume 22, Number 2, pp. 249-273, 2007.

Kernelizing PLS, Degrees of Freedom, and Efficient Model Selection
Nicole Krämer and Mikio L. Braun
In: International Comference on Machine Learning 2007, 20 - 24 June 2007, Corvallis, Oregon, USA.

ppls: penalized partial least squares
Nicole Krämer and Anne-Laure Boulesteix
(2007) The Comprehensive R Archive Network.

Analysis of High-Dimensional Data with Partial Least Squares and Boosting
Nicole Krämer
(2007) PhD thesis, TU Berlin.

Penalized Partial Least Squares with Applications to B-Splines Transformations and Functional Data
Nicole Krämer, Anne-Laure Boulesteix and Gerhard Tutz
submitted 2007.

Robustly estimating the flow direction of information in complex physical systems
Guido Nolte, Andreas Ziehe, Vadim Nikulin, Alois Schlögl, Nicole Krämer, Tom Brismar and Klaus-Robert Müller
arxiv 2007.

Partial Least Squares Regression for Graph Mining
Hiroto Saigo, Nicole Krämer and Koji Tsuda
In: 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2008), 24-27 Aug 2008, Las Vegas, USA.

Penalized Partial Least Squares with Applications to B-Spline Transformations and Functional Data
Nicole Krämer, Anne-Laure Boulesteix and Gerhard Tutz
Chemometrics & Intelligent Laboratory Systems Volume 94, Number 1, pp. 60-69, 2008.

Comments on: "Augmenting the Bootstrap to Analyze High-Dimensional Genomic Data"
Anne-Laure Boulesteix, Athanassios Kondylis and Nicole Krämer
TEST Volume 17, Number 1, pp. 31-35, 2008.

Robustly estimating the flow direction of information in complex physical systems
Guido Nolte, Andreas Ziehe, Vadim Nikulin, Alois Schlögl, Nicole Krämer, Tom Brismar and Klaus-Robert Müller
Physical Review Letters Volume 100, 234101, 2008.

Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression
Nicole Krämer, Masashi Sugiyama and Mikio braun
In: AISTATS 2009, 16-18 Apr 2009, Clearwater Beach, USA.

Comparison of Granger Causality and Phase Slope Index
Guido Nolte, Andreas Ziehe, Nicole Krämer, Florin Poupescu and Klaus-Robert Müller
In: NIPS08 workshop on Causality, 12 Dec 2008, Whistler, Canada.

Regularized Estimation of Large Scale Gene Association Networks using Gaussian Graphical Models
Nicole Krämer, Juliane Schäfer and Anne-Laure Boulesteix
BMC Bioinformatics Volume 10, Number 384, 2009.

Time Domain Parameters as a feature for EEG-Based Brain Computer Interfaces
Carmen Vidaurre, Nicole Krämer, Benjamin Blankertz and Alois Schlögl
Neural Networks Volume 22, Number 9, pp. 1313-1319, 2009.

The Feature Importance Ranking Measure
Alexander Zien, Nicole Krämer, Sören Sonnenburg and Gunnar Raetsch
In: European Conference on Machine Learning 2009, 7 - 11 September 2009, Bled, Slovenia.

The Degrees of Freedom of Partial Least Squares Regression
Nicole Krämer and Masashi Sugiyama
Journal of the American Statistical Association 2011.

ASAP: Automatic Semantics-Aware Analysis of Network Payloads
Tammo Krüger, Nicole Krämer and Konrad Rieck
European Conference on Machine Learning, Workshop on Privacy and Security Issues in Data Mining and Machine Learning 2011.

Optimal Learning Rates for Kernel Conjugate Gradient Regularization
Gilles Blanchard and Nicole Krämer
Advances in Neural Information Processing Systems (NIPS) Volume 23, 2010.

A Tutorial on the Use of Partial Least Squares and Principal Components Analysis for the Identification Problem in the Age-Period-Cohort-Analysis
Yu-Kang Tu, Nicole Krämer and Wen-Chung Lee
Epidemiology 2011. ISSN 1044-3983