Nico Goernitz
Nico Goernitz
former PostDoc @ Berlin Institute of Technology | now:
Verified email at - Homepage
Cited by
Cited by
Deep one-class classification
L Ruff, R Vandermeulen, N Goernitz, L Deecke, SA Siddiqui, A Binder, ...
International conference on machine learning, 4393-4402, 2018
Toward supervised anomaly detection
N Görnitz, MM Kloft, K Rieck, U Brefeld
Journal of Artificial Intelligence Research (JAIR), 2013
Deep semi-supervised anomaly detection
L Ruff, RA Vandermeulen, N Görnitz, A Binder, E Müller, KR Müller, ...
arXiv preprint arXiv:1906.02694, 2019
Active learning for network intrusion detection
N Görnitz, M Kloft, K Rieck, U Brefeld
Proceedings of the 2nd ACM workshop on Security and artificial intelligence …, 2009
Hidden markov anomaly detection
N Görnitz, M Braun, M Kloft
International Conference on Machine Learning, 2015
Active and semi-supervised data domain description
N Görnitz, M Kloft, U Brefeld
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2009
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation.
N Görnitz, C Widmer, G Zeller, A Kahles, S Sonnenburg, G Rätsch
NIPS, 2690-2698, 2011
Feature importance measure for non-linear learning algorithms
MMC Vidovic, N Görnitz, KR Müller, M Kloft
arXiv preprint arXiv:1611.07567, 2016
Support Vector Data Descriptions and-Means Clustering: One Class?
N Görnitz, LA Lima, KR Müller, M Kloft, S Nakajima
IEEE transactions on neural networks and learning systems 29 (9), 3994-4006, 2017
Learning and evaluation in presence of non-iid label noise
N Görnitz, A Porbadnigk, A Binder, C Sannelli, M Braun, KR Müller, ...
Artificial Intelligence and Statistics, 293-302, 2014
Efficient Algorithms for Exact Inference in Sequence Labeling SVMs
A Bauer, N Goernitz, F Biegler, KR Mueller, M Kloft
IEEE Transactions on Neural Networks and Learning (TNNLS), 2013
Efficient training of graph-regularized multitask SVMs
C Widmer, M Kloft, N Görnitz, G Rätsch
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012
Extracting latent brain states—Towards true labels in cognitive neuroscience experiments
AK Porbadnigk, N Görnitz, C Sannelli, A Binder, M Braun, M Kloft, ...
NeuroImage 120, 225-253, 2015
An off-the-shelf approach to authorship attribution
JA Nasir, N Görnitz, U Brefeld
Proceedings of COLING 2014, the 25th International Conference on …, 2014
Porosity estimation by semi-supervised learning with sparsely available labeled samples
LA Lima, N Görnitz, LE Varella, M Vellasco, KR Müller, S Nakajima
Computers & Geosciences 106, 33-48, 2017
Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis
VT Sreedharan, SJ Schultheiss, G Jean, A Kahles, R Bohnert, P Drewe, ...
Bioinformatics 30 (9), 1300-1301, 2014
Minimizing trust leaks for robust sybil detection
J Höner, S Nakajima, A Bauer, KR Müller, N Görnitz
International Conference on Machine Learning, 1520-1528, 2017
SVM2Motif—reconstructing overlapping DNA sequence motifs by mimicking an SVM predictor
MMC Vidovic, N Görnitz, KR Müller, G Rätsch, M Kloft
PloS one 10 (12), e0144782, 2015
Opening the black box: Revealing interpretable sequence motifs in kernel-based learning algorithms
MMC Vidovic, N Görnitz, KR Müller, G Rätsch, M Kloft
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
Ensembles of Lasso screening rules
S Lee, N Görnitz, EP Xing, D Heckerman, C Lippert
IEEE transactions on pattern analysis and machine intelligence 40 (12), 2841 …, 2017
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