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stat.ML2026
Learning Sparse Compositional Functions with Norm-Constrained Neural Networks
Shuo Huang, Lorenzo Fiorito, Lorenzo Rosasco +1
The ability of deep neural networks to learn hierarchical features is widely regarded as a key mechanism underlying their success in high-dimensional learning. Existing theory part…
cs.LG2026
Sparse-Aware Neural Networks for Nonlinear Functionals: Mitigating the Exponential Dependence on Dimension
Jianfei Li, Shuo Huang, Han Feng +2
Deep neural networks have emerged as powerful tools for learning operators defined over infinite-dimensional function spaces. However, existing theories frequently encounter diffic…