Active sampling for multiple output identification

Shai Fine*, Yishay Mansour

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)213-228
Number of pages16
JournalMachine Learning
Issue number2-3
StatePublished - Dec 2007


  • Active learning
  • Active sampling
  • Hitting
  • Output identification
  • Separation dimension
  • Transductive learning
  • VC dimension


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