Nico Görnitz

According to our database1, Nico Görnitz authored at least 28 papers between 2009 and 2020.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

2020
Deep Semi-Supervised Anomaly Detection.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
One-class classification in the presence of point, collective, and contextual anomalies.
PhD thesis, 2019

Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Transductive Regression for Data With Latent Dependence Structure.
IEEE Trans. Neural Networks Learn. Syst., 2018

Support Vector Data Descriptions and k-Means Clustering: One Class?
IEEE Trans. Neural Networks Learn. Syst., 2018

Ensembles of Lasso Screening Rules.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Unsupervised Detection and Explanation of Latent-class Contextual Anomalies.
CoRR, 2018

Deep One-Class Classification.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Porosity estimation by semi-supervised learning with sparsely available labeled samples.
Comput. Geosci., 2017

Optimizing for Measure of Performance in Max-Margin Parsing.
CoRR, 2017

Minimizing Trust Leaks for Robust Sybil Detection.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Feature Importance Measure for Non-linear Learning Algorithms.
CoRR, 2016

SynsetRank: Degree-adjusted Random Walk for Relation Identification.
CoRR, 2016

2015
Extracting latent brain states - Towards true labels in cognitive neuroscience experiments.
NeuroImage, 2015

Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Hidden Markov Anomaly Detection.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Efficient Algorithms for Exact Inference in Sequence Labeling SVMs.
IEEE Trans. Neural Networks Learn. Syst., 2014

Oqtans: a multifunctional workbench for RNA-seq data analysis.
BMC Bioinform., 2014

Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis.
Bioinform., 2014

An Off-the-shelf Approach to Authorship Attribution.
Proceedings of the COLING 2014, 2014

Learning and Evaluation in Presence of Non-i.i.d. Label Noise.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Decoding Brain States during Auditory Perception by Supervising Unsupervised Learning.
JCSE, 2013

Toward Supervised Anomaly Detection.
J. Artif. Intell. Res., 2013

2012
Efficient Training of Graph-Regularized Multitask SVMs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

2011
Oqtans: a Galaxy-integrated workflow for quantitative transcriptome analysis from NGS Data.
BMC Bioinform., 2011

Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2009
Active and Semi-supervised Data Domain Description.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Active learning for network intrusion detection.
Proceedings of the 2nd ACM Workshop on Security and Artificial Intelligence, 2009


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