Search Results for author: Eric Blais

Found 2 papers, 0 papers with code

VC Dimension and Distribution-Free Sample-Based Testing

no code implementations7 Dec 2020 Eric Blais, Renato Ferreira Pinto Jr., Nathaniel Harms

Conversely, we show that two natural classes of functions, juntas and monotone functions, can be tested with a number of samples that is polynomially smaller than the number of samples required for PAC learning.

PAC learning

Learning circuits with few negations

no code implementations30 Oct 2014 Eric Blais, Clément L. Canonne, Igor C. Oliveira, Rocco A. Servedio, Li-Yang Tan

In this paper we study the structure of Boolean functions in terms of the minimum number of negations in any circuit computing them, a complexity measure that interpolates between monotone functions and the class of all functions.

Learning Theory Negation

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