Article ID Journal Published Year Pages File Type
429866 Journal of Computer and System Sciences 2011 13 Pages PDF
Abstract

We show that unless NP = RP, it is hard to (even) weakly PAC-learn intersection of two halfspaces in Rn using a hypothesis which is a function of up to ℓ halfspaces (linear threshold functions) for any integer ℓ. Specifically, we show that for every integer ℓ and an arbitrarily small constant ε>0, unless NP = RP, no polynomial time algorithm can distinguish whether there is an intersection of two halfspaces that correctly classifies a given set of labeled points in Rn, or whether any function of ℓ halfspaces can correctly classify at most fraction of the points.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics