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SIAMCOMP
1998

Exact Learning of Discretized Geometric Concepts

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Exact Learning of Discretized Geometric Concepts
We first present an algorithm that uses membership and equivalence queries to exactly identify a discretized geometric concept defined by the union of m axis-parallel boxes in d-dimensional discretized Euclidean space where each coordinate can have n discrete values. This algorithm receives at most md counterexamples and uses time and membership queries polynomial in m and log n for any constant d. Furthermore, all equivalence queries can be formulated as the union of O(md log m) axis-parallel boxes. Next, we show how to extend our algorithm to efficiently learn, from only equivalence queries, 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 exactly learns (from equivalence queries only) unions of discretized axis-parallel boxes in constant dimensional space in polynomial time. Furthermore, this equivalence query only algorithm can be modified to ha...
Nader H. Bshouty, Paul W. Goldberg, Sally A. Goldm
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 1998
Where SIAMCOMP
Authors Nader H. Bshouty, Paul W. Goldberg, Sally A. Goldman, H. David Mathias
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