Projective DNF formulae and their revision
by
Robert H. Sloan
,
Balázs Szörényi
,
György Turán
| Venue: | In Learning Theory and Kernel Machines, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003 |
| Citations: | 2 - 1 self |
BibTeX
@INPROCEEDINGS{Sloan_projectivednf,
author = {Robert H. Sloan and Balázs Szörényi and György Turán},
title = {Projective DNF formulae and their revision},
booktitle = {In Learning Theory and Kernel Machines, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003},
year = {},
pages = {24--27},
publisher = {Springer}
}
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Abstract
Valiant argued that biology imposes various constraints on learnability, and, motivated by these constraints, introduced his model of projection learning [14]. Projection learning aims to learn a target concept over some large domain, in this paper {0, 1} n, by learning some of its projections to a class of smaller domains,
