curse-of-dimensionality

This paper establishes a theoretical framework showing that smooth activations in deep neural networks can mitigate the curse of dimensionality in uniform convergence, providing non-asymptotic guarantees and outperforming ReLU networks in worst-case reliability.

AdaGraph is a graph-native clustering algorithm that operates within the kNN graph topology to overcome the curse of dimensionality, validated across genomics, NLP, and materials science domains via the Structure-Centric Machine Learning paradigm.