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Evolutionary trees can be learned in polynomial time in the two-state general Markov model
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UNSPECIFIED (1998) Evolutionary trees can be learned in polynomial time in the two-state general Markov model. In: 39th Annual Symposium on Foundations of Computer Science, PALO ALTO, CA, NOV 08-11, 1998. Published in: 39TH ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE, PROCEEDINGS pp. 436-445.
Full text not available from this repository.Abstract
The j-State General Markov Model of evolution (due to Steel) is a stochastic model concerned with the evolution of strings over an alphabet of size j. In particular; the Two-State General Markov Model of evolution generalises the well-known Cavender-Farris-Neyman model of evolution by removing the symmetry restriction (which requires that the probability that a '0' turns into a '1' along mt edge is the same as the probability that a '1' turns into a '0' along the edge). Farach and Kannan showed how to PAC-learn Markov Evolutionary Trees in the Cavender-Farris-Neyman model provided that the target tree satisfies the additional restriction that all pairs of leaves hate a sufficiently high probability of being the same. We show how to remove both restrictions and thereby obtain the first polynomial-time PAC-learning algorithm (in the sense of Kearns et al.) far the general class of Two-State Markov Evolutionary Trees.
| Item Type: | Conference Item (UNSPECIFIED) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
| Series Name: | ANNUAL IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE |
| Journal or Publication Title: | 39TH ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE, PROCEEDINGS |
| Publisher: | IEEE COMPUTER SOC |
| ISBN: | 0-8186-9172-7 |
| ISSN: | 0272-5428 |
| Date: | 1998 |
| Number of Pages: | 4 |
| Page Range: | pp. 436-445 |
| Publication Status: | Published |
| Title of Event: | 39th Annual Symposium on Foundations of Computer Science |
| Location of Event: | PALO ALTO, CA |
| Date(s) of Event: | NOV 08-11, 1998 |
| URI: | http://wrap.warwick.ac.uk/id/eprint/15048 |
Data sourced from Thomson Reuters' Web of Knowledge
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