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Active sampling for multiple output identification

delete2007-10-02
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OA
AI
S
Shai Fine *
Y
Yishay Mansour
DOI：10.1007/s10994-007-5026-6delete
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Abstract

Abstract

En 中文
We study functions with multiple output values, and use active sampling to identify an example for each of the possible output values. Our results for this setting include: (1) Efficient active sampling algorithms for simple geometric concepts, such as intervals on a line and axis parallel boxes. (2) A characterization for the case of binary output value in a transductive setting. (3) An analysis of active sampling with uniform distribution in the plane. (4) An efficient algorithm for the Boolean hypercube when each output value is a monomial.
Keywords:
active learning
active sampling
hitting
VC dimension
transductive learning
output identification
separation dimension

Journal

Machine Learning cover
Machine Learning
IF:
2.9
Papers:
2.6K
Citations:
3.4W

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No organization information available