most citedRandom Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

cs.LG2023★ 2 cited

Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption

Vasilii Feofanov, Malik Tiomoko, Aladin Virmaux

We propose a theoretical framework to analyze semi-supervised classification under the low density separation assumption in a high-dimensional regime. In particular, we introduce Q…

math.CO2014

Non-commutative Frobenius characteristic of generalized parking functions -- Application to enumeration

Jean-Baptiste Priez, Aladin Virmaux

We give a recursive definition of generalized parking function that allows us to view them as a species. From there we compute a non-commutative characteristic of the generalized p…