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Sparse Input Features
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Sparse Input Features
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1 curated item1 Position
Updated about 18 hours ago
1 items · Sparse Input Features
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PositionMachine Learning
Prof. Dr. Barbara Hammer
Machine Learning Group, CITEC, Bielefeld University, Honda Research Institute Europe
Bielefeld University, D-33594 Bielefeld
Dec 5, 2025
The opening of a PhD position on the Topic of Machine Learning with Missing Features, as part of a newly established research project of the machine learning group at Bielefeld University and the Honda Research Institute (HRI) Europe in Offenbach. The aim is the development of machine learning methods that are suitable for variable or systematically sparse input features. Examples include models for personal data with partial information or technical applications with varying sensor equipment.