https://fuldok.hebis.de/xmlui/handle/fuldok/8 Sat, 02 May 2026 00:53:15 GMT 2026-05-02T00:53:15Z https://fuldok.hebis.de/xmlui/handle/fuldok/851 Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data Gepperth, Alexander; Pfülb, Benedikt We present an approach for efficiently training Gaussian Mixture Model (GMM) by Stochastic Gradient Descent (SGD) with non-stationary, high-dimensional streaming data. Our training scheme does not require data-driven parameter initialization (e.g., k-means) and can thus be trained based on a random initial state. Furthermore, the approach allows mini-batch sizes as low as 1, which are typical for streaming-data settings. Major problems in such settings are undesirable local optima during early training phases and numerical instabilities due to high data dimensionalities. We introduce an adaptive annealing procedure to address the first problem, whereas numerical instabilities are eliminated by an exponential-free approximation to the standard GMM log-likelihood. Experiments on a variety of visual and non-visual benchmarks show that our SGD approach can be trained completely without, for instance, k-means based centroid initialization. It also compares favorably to an online variant of Expectation-Maximization (EM)—stochastic EM (sEM), which it outperforms by a large margin for very high-dimensional data. Tue, 17 Aug 2021 00:00:00 GMT https://fuldok.hebis.de/xmlui/handle/fuldok/851 2021-08-17T00:00:00Z https://fuldok.hebis.de/xmlui/handle/fuldok/838 Pure Functions in C: A Small Keyword for AutomaticParallelization Süß,Tim; NagelLars; Vef,Marc-André; Brinkmann, André; Feld, Dustin; Soddemann,Thomas The need for parallel task execution has been steadily growing in recent years since manufacturers mainly improve processor performance by increasing the number of installed cores instead of scaling the processor’s frequency. To make use of this potential, an essential technique to increase the parallelism of a program is to parallelize loops. Several automatic loop nest parallelizers have been developed in the past such as PluTo. The main restriction of these tools is that the loops must be statically analyzable which, among other things, disallows function calls within the loops. In this article, we present a seemingly simple extension to the C programming language which marks functions without side-effects. These functions can then basically beignored when the automatic parallelizer checks the parallelizability of loops. We integrated the approach into the GCC compiler toolchain and evaluated it by running several real-world applications. Our experiments show that the C extension helps to identify additional parallelization opportunities and, thus, to significantly increase the performance of applications. Sat, 30 May 2020 00:00:00 GMT https://fuldok.hebis.de/xmlui/handle/fuldok/838 2020-05-30T00:00:00Z https://fuldok.hebis.de/xmlui/handle/fuldok/680 Acceptance of Robots in Nursing Environment Herpers, Martine (Prof. Dr.) Research questions: What is the variety of robots used in nursing environment? How can the acceptance of robots by nurses be measured? a large variety of robots are used in nursing environment: from humanoid robot until robotic devices. The questionnaire has to take the professional environment and the distance from nurses to robots into account. The Almere Model was used to complement questions using 5 point Likert scale for measuring the acceptance of the robots. Fri, 02 Aug 2024 00:00:00 GMT https://fuldok.hebis.de/xmlui/handle/fuldok/680 2024-08-02T00:00:00Z https://fuldok.hebis.de/xmlui/handle/fuldok/679 Acceptance of Robots in Nursing Environment – Proposed Design of Questionnaire for Nurses Herpers, Martine (Prof. Dr.) Robotics and AI offer many opportunities to make nursing work easier. Those receiving care must accept this support, but it must also fit into the processes of professional care. In this first study, we present the variety of robots and suggest questions for nurses to determine their needs. Fri, 02 Aug 2024 00:00:00 GMT https://fuldok.hebis.de/xmlui/handle/fuldok/679 2024-08-02T00:00:00Z