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On learning discretized geometric concepts

Bshouty, N.H.   Zhixiang Chen   Homer, S.  
Dept. of Comput. Sci., Calgary Univ., Alta.;

This paper appears in: Foundations of Computer Science, 1994 Proceedings., 35th Annual Symposium on
Publication Date: 20-22 Nov 1994
On page(s): 54-63
Meeting Date: 11/20/1994 - 11/22/1994
Location: Santa Fe, NM, USA
ISBN: 0-8186-6580-7
References Cited: 20
INSPEC Accession Number: 4865015
DOI: 10.1109/SFCS.1994.365705
Posted online: 2002-08-06 19:20:36.0

Abstract
We present a polynomial time online learning algorithm that learns any discretized geometric concept generated from any number of halfspaces with any number of known (to the learner) slopes in a constant dimensional space. In particular, our algorithm learns (from equivalence queries only) unions of discretized axis-parallel rectangles in a constant dimensional space in polynomial time. The algorithm also runs in polynomial time in l if the teacher lies on l counterexamples. We then show a PAC-learning algorithm for the above discretized geometric concept when the example oracle lies on the labels of the examples with a fixed probability p⩽½-1/r that runs in polynomial time also with r. We use these methods, as well as a bounded version of the finite injury priority method, to construct algorithms for learning several classes of rectangles. In particular we design efficient algorithms for learning several classes of unions of discretized axis-parallel rectangles in either arbitrary dimensional spaces or constant dimensional spaces

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