A weighted sum of cross-entropy and a PCA-condensed, per-cluster-variance Magnet loss with dynamic alpha and beta schedules improves accuracy and latent cluster quality on three image benchmarks.
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Enhancing Interpretability Through Loss-Defined Classification Objective in Structured Latent Spaces
A weighted sum of cross-entropy and a PCA-condensed, per-cluster-variance Magnet loss with dynamic alpha and beta schedules improves accuracy and latent cluster quality on three image benchmarks.