2 citations · 8 across the 16 of their papers we have counts for
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stat.ML2021
Understanding neural networks with reproducing kernel Banach spaces
Francesca Bartolucci, Ernesto De Vito, Lorenzo Rosasco +1
Characterizing the function spaces corresponding to neural networks can provide a way to understand their properties. In this paper we discuss how the theory of reproducing kernel…
stat.ML2021
ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions
Luigi Carratino, Stefano Vigogna, Daniele Calandriello +1
We introduce ParK, a new large-scale solver for kernel ridge regression. Our approach combines partitioning with random projections and iterative optimization to reduce space and t…
stat.ML2021★ 2 cited
Multiscale regression on unknown manifolds
Wenjing Liao, Mauro Maggioni, Stefano Vigogna
We consider the regression problem of estimating functions on but supported on a -dimensional manifold with . Draw…