Abstract: Active learning provides guidance for the design and modeling of systems with highly expensive sampling costs. However, existing active learning approaches suffer from cold-start concerns, ...
Abstract: Tiny machine learning (TinyML) is a new frontier of machine learning. By squeezing deep learning models into billions of IoT devices and microcontrollers (MCUs), we expand the scope of ...
The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...
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