Derives approximation rates and excess risk bounds for Frobenius norm-constrained DNNs learning sparse compositional functions on DAGs, applicable to multi-index models and binary trees while avoiding the curse of dimensionality.
Position: A theory of deep learning must include compositional sparsity.arXiv preprint arXiv:2507.02550, 2025
2 Pith papers cite this work. Polarity classification is still indexing.
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