Active Sampling for Multiple Output Identification

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.

• Type: Conference
• Year: 2006
• Where: COLT
• Authors: Shai Fine, Yishay Mansour
• Keywords: Active Sampling, COLT 2006, Machine Learning, Multiple Output Values, Output Value