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20162022
most citedBeating SGD Saturation with Tail-Averaging and Minibatching

5 citations · 7 across the 5 of their papers we have counts for

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Showing 2019Show all

2 papers · 1 filter

math.FA2019

Reproducing kernel Hilbert spaces on manifolds: Sobolev and Diffusion spaces

Ernesto De Vito, Nicole Mücke, Lorenzo Rosasco

We study reproducing kernel Hilbert spaces (RKHS) on a Riemannian manifold. In particular, we discuss under which condition Sobolev spaces are RKHS and characterize their reproduci…

stat.ML2019★ 5 cited

Beating SGD Saturation with Tail-Averaging and Minibatching

Nicole Mücke, Gergely Neu, Lorenzo Rosasco

While stochastic gradient descent (SGD) is one of the major workhorses in machine learning, the learning properties of many practically used variants are poorly understood. In this…