Author

Canlin Zhang

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#artificial intelligence Preprint Oct 2026

Neural Expansion: A Unified Mechanism for How Deep Neural Networks Generalize

Deep neural networks demonstrate remarkable generalization despite being highly over-parameterized, challenging traditional statistical learning theories. While several theoretical paradigms such as margin-based bounds, PAC-Bayesian analyses, and neural tangent kernels provide global explanations, they often lack mecha...

Chashi Mahiul Islam, Samuel Jacob Chacko, Mao Nishino et al. · 0 citations

#machine learning Jul 2026

Converge to Surprise: Evolutionary Self-supervised Image Clustering

This work proposes the converge-to-surprise scheme to optimize a model: an evolution-strategy (ES) outer loop, which maximizes the surprise score using the mutation-selection mechanism, paired with a periodic gradient-descent inner loop, which uses the surprising clusters already discovered by ES as surrogate targets.

Canlin Zhang, Xiuwen Liu · arXiv.org · 0 citations