Learning convex polytopes with margin

NeurIPS 2018 Lee-Ad GottliebEran KaufmanAryeh KontorovichGabriel Nivasch

We present an improved algorithm for properly learning convex polytopes in the realizable PAC setting from data with a margin. Our learning algorithm constructs a consistent polytope as an intersection of about $t \log t$ halfspaces with margins in time polynomial in $t$ (where $t$ is the number of halfspaces forming an optimal polytope)... (read more)

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