IEEE

Continual Learning for Object Classification: Integrating AutoML for Binary Classification Tasks Within a Modular Dynamic Architecture

Abstract: For humans it is quite easy to identify a new object after learning to identify existing ones, but not for a machine. Deep neural networks (DNN) are the foundation of the current ...
IEEE

Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL

Abstract: While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, a recent trend in AutoML is to focus on neural architecture search. In this paper, we ...