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Dataset Pruning from First Principles: A Label-Free Linear Programming Approach

arXiv:2610.10347v1 Announce Type: new Abstract: Dataset pruning reduces a large training set to a representative subset while preserving model performance. Existing geometry-based methods typically assume that nearby points in embedding space share similar properties. Rather than imposing this assu…

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  1. 2026-10-08 04:00 · arXiv stat.ML
    Dataset Pruning from First Principles: A Label-Free Linear Programming Approach

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