Search Results for author: Nathanael Ackerman

Found 3 papers, 0 papers with code

On computable learning of continuous features

no code implementations24 Nov 2021 Nathanael Ackerman, Julian Asilis, Jieqi Di, Cameron Freer, Jean-Baptiste Tristan

We introduce definitions of computable PAC learning for binary classification over computable metric spaces.

Binary Classification PAC learning

Priors on exchangeable directed graphs

no code implementations28 Oct 2015 Diana Cai, Nathanael Ackerman, Cameron Freer

Directed graphs occur throughout statistical modeling of networks, and exchangeability is a natural assumption when the ordering of vertices does not matter.

An iterative step-function estimator for graphons

no code implementations5 Dec 2014 Diana Cai, Nathanael Ackerman, Cameron Freer

Exchangeable graphs arise via a sampling procedure from measurable functions known as graphons.

Clustering Graphon Estimation

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