1 code implementation • ICML 2018 • Lukas Ruff, Robert Vandermeulen, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel Müller, Marius Kloft
Despite the great advances made by deep learning in many machine learning problems, there is a relative dearth of deep learning approaches for anomaly detection.
Ranked #32 on Anomaly Detection on One-class CIFAR-10
no code implementations • 2 Sep 2016 • Shinichi Nakajima, Sebastian Krause, Dirk Weissenborn, Sven Schmeier, Nico Goernitz, Feiyu Xu
In relation extraction, a key process is to obtain good detectors that find relevant sentences describing the target relation.
no code implementations • 23 Jan 2014 • Nico Goernitz, Marius Micha Kloft, Konrad Rieck, Ulf Brefeld
Anomaly detection is being regarded as an unsupervised learning task as anomalies stem from adversarial or unlikely events with unknown distributions.
1 code implementation • 20 Sep 2013 • Georg Zeller, Nico Goernitz, Andre Kahles, Jonas Behr, Pramod Mudrakarta, Soeren Sonnenburg, Gunnar Raetsch
Recent advances in high-throughput cDNA sequencing (RNA-Seq) technology have revolutionized transcriptome studies.
no code implementations • NeurIPS 2011 • Nico Goernitz, Christian Widmer, Georg Zeller, Andre Kahles, Gunnar Rätsch, Sören Sonnenburg
We present a novel regularization-based Multitask Learning (MTL) formulation for Structured Output (SO) prediction for the case of hierarchical task relations.