7 citations · 8 across the 3 of their papers we have counts for
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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…
stat.ML2019★ 7 cited
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric +2
Gaussian processes (GP) are a well studied Bayesian approach for the optimization of black-box functions. Despite their effectiveness in simple problems, GP-based algorithms hardly…