Active sampling for multiple output identification

  • Authors:
  • Shai Fine;Yishay Mansour

  • Affiliations:
  • IBM Research Laboratory in Haifa, Israel;School of Computer Science, Tel Aviv University, Tel Aviv, Israel

  • Venue:
  • COLT'06 Proceedings of the 19th annual conference on Learning Theory
  • Year:
  • 2006
  • Finding the Rare Cube

    ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory

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Abstract

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.