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Collaborative Research Center SFB 876 - Providing Information by Resource-Constrained Data Analysis


The collaborative research center SFB876 brings together data mining and embedded systems. On the one hand, embedded systems can be further improved using machine learning. On the other hand, data mining algorithms can be realized in hardware, e.g. FPGAs, or run on GPGPUs. The restrictions of ubiquitous systems in computing power, memory, and energy demand new algorithms for known learning tasks. These resource bounded learning algorithms may also be applied on extremely large data bases on servers.
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Call for Papers: Workshop on Machine Learning for Astroparticle Physics and Astronomy (ml.astro) by SFB876 - Project C3

Project C3 is proud to announce their "Workshop on Machine Learning for Astroparticle Physics and Astronomy" (ml.astro), co-located with INFORMATIK 2022. 

The workshop will be held on September 26th 2022 in Hamburg, Germany and include invited as well as contributed talks. Contributions should be submitted as full papers of 6 to 10 pages until April 30th 2022 and may include, without being limited to, the following topics:

Machine learning applications in astroparticle physics and astronomy; Unfolding / deconvolution / quantification; Neural networks and graph neural networks (GNNs); Generative adversarial networks (GANs); Ensemble Methods; Unsupervised learning; Unsupervised domain adaptation; Active class selection; Imbalanced learning; Learning with domain knowledge; Particle reconstruction, tracking, and classification; Monte Carlo simulations Further information on the timeline and the submission of contributions is provided via the workshop website: https://sfb876.tu-dortmund.de/ml.astro/

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