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Electronic Colloquium on Computational Complexity

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Reports tagged with Hardness of Learning:
TR10-185 | 2nd December 2010
Vitaly Feldman, Venkatesan Guruswami, Prasad Raghavendra, Yi Wu

Agnostic Learning of Monomials by Halfspaces is Hard

We prove the following strong hardness result for learning: Given a distribution of labeled examples from the hypercube such that there exists a monomial consistent with $(1-\epsilon)$ of the examples, it is $\mathrm{NP}$-hard to find a halfspace that is correct on $(1/2+\epsilon)$ of the examples, for arbitrary constants $\epsilon ... more >>>

TR14-063 | 23rd April 2014
Adam Klivans, Pravesh Kothari

Embedding Hard Learning Problems into Gaussian Space

We give the first representation-independent hardness result for agnostically learning halfspaces with respect to the Gaussian distribution. We reduce from the problem of learning sparse parities with noise with respect to the uniform distribution on the hypercube (sparse LPN), a notoriously hard problem in computer science and show that ... more >>>

ISSN 1433-8092 | Imprint