30 citations · 112 across the 22 of their papers we have counts for
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cs.LG2019★ 30 cited
Intrinsic dimension estimation for locally undersampled data
Vittorio Erba, Marco Gherardi, Pietro Rotondo
High-dimensional data are ubiquitous in contemporary science and finding methods to compress them is one of the primary goals of machine learning. Given a dataset lying in a high-d…
cond-mat.dis-nn2019★ 9 cited
The Dyck bound in the concave 1-dimensional random assignment model
Sergio Caracciolo, Matteo P. D'Achille, Vittorio Erba +1
We consider models of assignment for random blue points and red points on an interval of length , in which the cost for connecting a blue point in to a red point in…