Agnostic Active Learning Without Constraints

Details Agnostic Active Learning Without Constraints Agnostic Active Learning Without Constraints

2010-06-14

arxiv.org/abs/1006.2588v1

Computer Science

Learning

Scientific paper

We present and analyze an agnostic active learning algorithm that works without keeping a version space. This is unlike all previous approaches where a restricted set of candidate hypotheses is maintained throughout learning, and only hypotheses from this set are ever returned. By avoiding this version space approach, our algorithm sheds the computational burden and brittleness associated with maintaining version spaces, yet still allows for substantial improvements over supervised learning for classification.

Affiliated with

Also associated with

No associations

Rating

Agnostic Active Learning Without Constraints does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Agnostic Active Learning Without Constraints, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Agnostic Active Learning Without Constraints will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-421382