Nicole Krämer

Orcid: 0000-0002-8209-9141

Affiliations:
  • Staburo GmbH, Munich, Germany
  • TU München, Department of Mathematics, Munich, Germany (former)
  • Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany (former)
  • Berlin Institute of Technology, Machine Learning Group, Germany (former)


According to our database1, Nicole Krämer authored at least 14 papers between 2005 and 2012.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2012
Learning stateful models for network honeypots.
Proceedings of the 5th ACM Workshop on Security and Artificial Intelligence, 2012

2010
Comparison of Granger Causality and Phase Slope Index.
Proceedings of the Causality: Objectives and Assessment (NIPS 2008 Workshop), 2010

Sparse Causal Discovery in Multivariate Time Series.
Proceedings of the Causality: Objectives and Assessment (NIPS 2008 Workshop), 2010

Kernel Partial Least Squares is Universally Consistent.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

ASAP: Automatic Semantics-Aware Analysis of Network Payloads.
Proceedings of the Privacy and Security Issues in Data Mining and Machine Learning, 2010

Optimal learning rates for Kernel Conjugate Gradient regression.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Time Domain Parameters as a feature for EEG-based Brain-Computer Interfaces.
Neural Networks, 2009

Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Regularized estimation of large-scale gene association networks using graphical Gaussian models.
BMC Bioinform., 2009

The Feature Importance Ranking Measure.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

2008
Partial least squares regression for graph mining.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

2007
An overview on the shrinkage properties of partial least squares regression.
Comput. Stat., 2007

Kernelizing PLS, degrees of freedom, and efficient model selection.
Proceedings of the Machine Learning, 2007

2005
Overview and Recent Advances in Partial Least Squares.
Proceedings of the Subspace, 2005


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