arXiv Machine Learning September 18, 2026 By Poowanut Niamluang, Jittat Fakcharoenphol

Subdomain-aware representation compression for pretrained image embeddings

Read the original on arXiv Machine Learning →

The paper explores subdomain-aware dimensionality reduction for pretrained image embeddings, applying techniques such as PCA and LDA to compress representations within specific image subdomains. Results show that this targeted compression reduces space and computational complexity while improving accuracy compared to using full embeddings. Additionally, the study demonstrates that the compressed representations retain transfer learning capabilities across tasks.

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