Department of Mathematics, Technische Universität München
List of publications from the DBLP Bibliography Server - FAQ
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 | 2012 | |
|---|---|---|
| c9 |      | Tammo Krueger, Hugo Gascon, Nicole Krämer, Konrad Rieck: Learning stateful models for network honeypots. AISec 2012: 37-48 |
| 2011 | ||
| c8 | | Kathrin Maria Gerling, Alberto Fuchslocher, Ralf Schmidt, Nicole Krämer, Maic Masuch: Designing and Evaluating Casual Health Games for Children and Teenagers with Cancer. ICEC 2011: 198-209 |
| c7 | | Alberto Fuchslocher, Kathrin Maria Gerling, Maic Masuch, Nicole Krämer: Evaluating social games for kids and teenagers diagnosed with cancer. SeGAH 2011: 1-4 |
| 2010 | ||
| j6 | | Stefan Haufe, Klaus-Robert Müller, Guido Nolte, Nicole Krämer: Sparse Causal Discovery in Multivariate Time Series. Journal of Machine Learning Research - Proceedings Track 6: 97-106 (2010) |
| j5 | | Guido Nolte, Andreas Ziehe, Nicole Krämer, Florin Popescu, Klaus-Robert Müller: Comparison of Granger Causality and Phase Slope Index. Journal of Machine Learning Research - Proceedings Track 6: 267-276 (2010) |
| j4 | | Gilles Blanchard, Nicole Krämer: Kernel Partial Least Squares is Universally Consistent. Journal of Machine Learning Research - Proceedings Track 9: 57-64 (2010) |
| c6 | | Gilles Blanchard, Nicole Krämer: Optimal learning rates for Kernel Conjugate Gradient regression. NIPS 2010: 226-234 |
| c5 | | Tammo Krueger, Nicole Krämer, Konrad Rieck: ASAP: Automatic Semantics-Aware Analysis of Network Payloads. PSDML 2010: 50-63 |
| 2009 | ||
| j3 | | Nicole Krämer, Juliane Schäfer, Anne-Laure Boulesteix: Regularized estimation of large-scale gene association networks using graphical Gaussian models. BMC Bioinformatics 10: 384 (2009) |
| j2 | | Nicole Krämer, Masashi Sugiyama, Mikio L. Braun: Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression. Journal of Machine Learning Research - Proceedings Track 5: 288-295 (2009) |
| j1 | | Carmen Vidaurre, Nicole Krämer, Benjamin Blankertz, Alois Schlögl: Time Domain Parameters as a feature for EEG-based Brain-Computer Interfaces. Neural Networks 22(9): 1313-1319 (2009) |
| c4 | | Alexander Zien, Nicole Krämer, Sören Sonnenburg, Gunnar Rätsch: The Feature Importance Ranking Measure. ECML/PKDD (2) 2009: 694-709 |
| 2008 | ||
| c3 | | Hiroto Saigo, Nicole Krämer, Koji Tsuda: Partial least squares regression for graph mining. KDD 2008: 578-586 |
| 2007 | ||
| c2 | | Nicole Krämer, Mikio L. Braun: Kernelizing PLS, degrees of freedom, and efficient model selection. ICML 2007: 441-448 |
| 2005 | ||
| c1 | | Roman Rosipal, Nicole Krämer: Overview and Recent Advances in Partial Least Squares. SLSFS 2005: 34-51 |
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