Project Details
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Autonomous and Efficiently Scalable Deep Learning

Subject Area Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
Term from 2014 to 2020
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 260197604
 
Final Report Year 2019

Final Report Abstract

In summary, the project was not only successful in taking important steps towards more autonomous systems, that are able to learn from as little data as possible in a mathematically grounded fashion. But it also importantly contributed to spread light on a severe general issue in semi-supervised learning, that is the need to take validation data into account when comparing systems that learn on few labeled data. Furthermore, novel developments on efficient scaling enabled the developed NeSi networks to be applicable at realistic scales and with many parameters. Furthermore, the scalability methods applied gave rise to novel and more broadly applicable learning algorithms.

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Additional Information

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