Provable Data Scaling Law
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Provable Data Scaling Law for Meta Learning via Complexity Minimization
arXiv:2606.02008v1 Announce Type: cross Abstract: Pre-training has become a fundamental paradigm in modern machine learning, with one of its key empirical benefits being reduced downstream sample complexity as the scale of pre-training data increases. However, existing theoretical frameworks for pre-training do not fully explain this phenomenon. In this paper, we introduce complexity minimization, a novel meta-representation learning framework designed to enable theoretical analysis of this...
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Publication history - Interzone #215, April 2008. - Free podcast at Transmissions From Beyond. [Site no longer active] - Oceanic (collection, Orion) -