A benchmark of supervised, self-supervised, and semi-supervised contrastive learning on CIFAR-10 and EuroSAT shows labeling energy can dominate training energy, with semi-supervised CCSSL providing a favorable accuracy-energy trade-off.
A simple framework for contrastive learning of visual representations,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Self-Supervised Learning at the Edge: The Cost of Labeling
A benchmark of supervised, self-supervised, and semi-supervised contrastive learning on CIFAR-10 and EuroSAT shows labeling energy can dominate training energy, with semi-supervised CCSSL providing a favorable accuracy-energy trade-off.