AINeutralarXiv – CS AI · May 296/10
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How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions
Researchers demonstrate that neural scaling laws and the Vendi Score—two methods for evaluating dataset quality—are both submodular functions, enabling optimization via a broader class of matrix spectral functions. By developing efficient secular-equation-based updates, they achieve 35,000x speedup in computations, making direct optimization feasible on large-scale datasets and revealing that facility location outperforms other objectives for predicting training subset value.