On Sequence Prediction for Arbitrary Measures

Details On Sequence Prediction for Arbitrary Measures On Sequence Prediction for Arbitrary Measures

2006-06-16

arxiv.org/abs/cs/0606077v1

Proc. IEEE International Symposium on Information Theory (ISIT 2007) pages 2346-2350

Computer Science

Learning

16 pages

Scientific paper

Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequences and consider the question when one of the measures predicts the other, that is, when conditional probabilities converge (in a certain sense) when one of the measures is chosen to generate the sequence. This question may be considered a refinement of the problem of sequence prediction in its most general formulation: for a given class of probability measures, does there exist a measure which predicts all of the measures in the class? To address this problem, we find some conditions on local absolute continuity which are sufficient for prediction and which generalize several different notions which are known to be sufficient for prediction. We also formulate some open questions to outline a direction for finding the conditions on classes of measures for which prediction is possible.

Affiliated with

Also associated with

No associations

Rating

On Sequence Prediction for Arbitrary Measures 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 On Sequence Prediction for Arbitrary Measures, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On Sequence Prediction for Arbitrary Measures will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-390044