3 papers
cs.LG2016
Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions
Christian Gruhl, Bernhard Sick
Hidden Markov Models (HMM) have been used for several years in many time series analysis or pattern recognitions tasks. HMM are often trained by means of the Baum-Welch algorithm w…
cs.LG2016
Towards Automation of Knowledge Understanding: An Approach for Probabilistic Generative Classifiers
Dominik Fisch, Christian Gruhl, Edgar Kalkowski +2
After data selection, pre-processing, transformation, and feature extraction, knowledge extraction is not the final step in a data mining process. It is then necessary to understan…
cs.LG2016
Detecting Novel Processes with CANDIES -- An Holistic Novelty Detection Technique based on Probabilistic Models
Christian Gruhl, Bernhard Sick
In this article, we propose CANDIES (Combined Approach for Novelty Detection in Intelligent Embedded Systems), a new approach to novelty detection in technical systems. We assume t…