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What and Who

Learning mixture of mutagnetic trees

Junming Yin
IMPRS
IMPRS Masters' Lunch
AG 1, AG 2, AG 3, AG 4, AG 5  
AG Audience

Date, Time and Location

Tuesday, 13 July 2004
13:00
60 Minutes
46.1 - MPII
024
Saarbrücken

Abstract

Based on HIV's high rate of replication and mutation, it is able to escape
from drug pressure by developing drug resistance. Mutational patterns causing
resistance have been identified by several machine learning methods. But how
resistance-associated mutations accumulate is not well studied. Characterizing
the accumulation will help us to understand the virus' evolutionary
process.

A new model, namely mixture of mutagnetic trees, based on EM-like
algorithm has been proposed to tackle this problem. In order to improve
the results, we will incorporate a regularization framework for the
mixture model, which is applicable to the procedure of model selection.
Furthermore, we will propose a measurement of distance between two models to
validate the stability of mixture of trees and our algorithm.

Contact

Kerstin Meyer-Ross
0681 - 9325 226
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logged in users only

Christine Kiesel, 07/08/2004 09:06
Christine Kiesel, 07/02/2004 09:18
Christine Kiesel, 06/22/2004 10:04
Christine Kiesel, 06/14/2004 10:57
Christine Kiesel, 06/02/2004 11:12
Christine Kiesel, 05/26/2004 10:09
Christine Kiesel, 05/10/2004 12:50
Christine Kiesel, 05/10/2004 12:48 -- Created document.