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Nico Görnitz
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2020 – today
- 2020
- [j12]Alexander Bauer
, Shinichi Nakajima, Nico Görnitz
Optimizing for Measure of Performance in Max-Margin Parsing. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2680-2684 (2020) - [c13]Lukas Ruff, Robert A. Vandermeulen
Deep Semi-Supervised Anomaly Detection. ICLR 2020
2010 – 2019
- 2019
- [b1]Nico Görnitz:
One-class classification in the presence of point, collective, and contextual anomalies. Technical University of Berlin, Germany, 2019 - [c12]Alexander Bauer, Shinichi Nakajima, Nico Görnitz, Klaus-Robert Müller:
Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs. AISTATS 2019: 1696-1703 - [i7]Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft:
Deep Semi-Supervised Anomaly Detection. CoRR abs/1906.02694 (2019) - 2018
- [j11]Seunghak Lee
Ensembles of Lasso Screening Rules. IEEE Trans. Pattern Anal. Mach. Intell. 40(12): 2841-2852 (2018) - [j10]Nico Görnitz
Transductive Regression for Data With Latent Dependence Structure. IEEE Trans. Neural Networks Learn. Syst. 29(7): 2743-2756 (2018) - [j9]Nico Görnitz
Support Vector Data Descriptions and k-Means Clustering: One Class? IEEE Trans. Neural Networks Learn. Syst. 29(9): 3994-4006 (2018) - [c11]Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, Marius Kloft:
Deep One-Class Classification. ICML 2018: 4390-4399 - [i6]Jacob R. Kauffmann, Grégoire Montavon, Luiz Alberto Lima, Shinichi Nakajima, Klaus-Robert Müller, Nico Görnitz:
Unsupervised Detection and Explanation of Latent-class Contextual Anomalies. CoRR abs/1806.11326 (2018) - 2017
- [j8]Luiz Alberto Lima, Nico Görnitz, Luiz Eduardo Varella, Marley M. B. R. Vellasco
Porosity estimation by semi-supervised learning with sparsely available labeled samples. Comput. Geosci. 106: 33-48 (2017) - [c10]János Höner, Shinichi Nakajima, Alexander Bauer, Klaus-Robert Müller, Nico Görnitz:
Minimizing Trust Leaks for Robust Sybil Detection. ICML 2017: 1520-1528 - [i5]Alexander Bauer, Shinichi Nakajima, Nico Görnitz, Klaus-Robert Müller:
Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs. CoRR abs/1708.03314 (2017) - [i4]Alexander Bauer, Shinichi Nakajima, Nico Görnitz, Klaus-Robert Müller:
Optimizing for Measure of Performance in Max-Margin Parsing. CoRR abs/1709.01562 (2017) - 2016
- [i3]Shinichi Nakajima, Sebastian Krause, Dirk Weissenborn, Sven Schmeier, Nico Görnitz, Feiyu Xu:
SynsetRank: Degree-adjusted Random Walk for Relation Identification. CoRR abs/1609.00626 (2016) - [i2]Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller, Marius Kloft:
Feature Importance Measure for Non-linear Learning Algorithms. CoRR abs/1611.07567 (2016) - 2015
- [j7]Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder
Extracting latent brain states - Towards true labels in cognitive neuroscience experiments. NeuroImage 120: 225-253 (2015) - [c9]Nico Görnitz, Mikio L. Braun, Marius Kloft:
Hidden Markov Anomaly Detection. ICML 2015: 1833-1842 - [c8]Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller
Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms. ECML/PKDD (2) 2015: 137-153 - 2014
- [j6]Vipin T. Sreedharan, Sebastian J. Schultheiß
Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis. Bioinform. 30(9): 1300-1301 (2014) - [j5]Vipin T. Sreedharan, Sebastian J. Schultheiß
Oqtans: a multifunctional workbench for RNA-seq data analysis. BMC Bioinform. 15(S-3): A7 (2014) - [j4]Alexander Bauer, Nico Görnitz, Franziska Biegler, Klaus-Robert Müller
Efficient Algorithms for Exact Inference in Sequence Labeling SVMs. IEEE Trans. Neural Networks Learn. Syst. 25(5): 870-881 (2014) - [c7]Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller, Marius Kloft:
Learning and Evaluation in Presence of Non-i.i.d. Label Noise. AISTATS 2014: 293-302 - [c6]Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder
When brain and behavior disagree: Tackling systematic label noise in EEG data with machine learning. BCI 2014: 1-4 - [c5]Jamal Abdul Nasir, Nico Görnitz, Ulf Brefeld:
An Off-the-shelf Approach to Authorship Attribution. COLING 2014: 895-904 - [i1]Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld:
Toward Supervised Anomaly Detection. CoRR abs/1401.6424 (2014) - 2013
- [j3]Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld:
Toward Supervised Anomaly Detection. J. Artif. Intell. Res. 46: 235-262 (2013) - [j2]Anne Porbadnigk, Nico Görnitz, Marius Kloft, Klaus-Robert Müller
Decoding Brain States during Auditory Perception by Supervising Unsupervised Learning. J. Comput. Sci. Eng. 7(2): 112-121 (2013) - 2012
- [c4]Christian Widmer, Marius Kloft, Nico Görnitz, Gunnar Rätsch
Efficient Training of Graph-Regularized Multitask SVMs. ECML/PKDD (1) 2012: 633-647 - 2011
- [j1]Sebastian J. Schultheiß
Oqtans: a Galaxy-integrated workflow for quantitative transcriptome analysis from NGS Data. BMC Bioinform. 12(S-11): A7 (2011) - [c3]Nico Görnitz, Christian Widmer, Georg Zeller, André Kahles, Sören Sonnenburg, Gunnar Rätsch:
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation. NIPS 2011: 2690-2698
2000 – 2009
- 2009
- [c2]Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld:
Active learning for network intrusion detection. AISec 2009: 47-54 - [c1]Nico Görnitz, Marius Kloft, Ulf Brefeld:
Active and Semi-supervised Data Domain Description. ECML/PKDD (1) 2009: 407-422
Coauthor Index
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