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cs.LG2024
SUPClust: Active Learning at the Boundaries
Yuta Ono, Till Aczel, Benjamin Estermann +1
Active learning is a machine learning paradigm designed to optimize model performance in a setting where labeled data is expensive to acquire. In this work, we propose a novel acti…
cs.LG2023★ 3 cited
DAVA: Disentangling Adversarial Variational Autoencoder
Benjamin Estermann, Roger Wattenhofer
The use of well-disentangled representations offers many advantages for downstream tasks, e.g. an increased sample efficiency, or better interpretability. However, the quality of d…