A subject-reweighted contrastive loss improves cross-subject generalization for human activity recognition across unimodal, multimodal, and supervised settings.
Contrastive Learning and HAR Contrastive loss maps semantically similar (positive) samples closer in the embedding space while pushing dissimilar (negative) samples farther apart
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Subject Invariant Contrastive Learning for Human Activity Recognition
A subject-reweighted contrastive loss improves cross-subject generalization for human activity recognition across unimodal, multimodal, and supervised settings.