Machine Learning under Resource Constraints - Applications

Machine Learning under Resource Constraints - ApplicationsMachine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a

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Karl-Siegbert Rehberg (TU Dresden) mit der externen Prüfung des Sachverhalts beauftragt

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