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Summary: ADAPTIVE UPDATES FOR MAP CONFIGURATIONS WITH APPLICATIONS TO
BIOINFORMATICS
Umut A. Acar Alexander T. Ihler Ramgopal R. Mettu ĻOzgĻur SĻumer
Toyota Tech. Institute U.C. Irvine Univ. of Massachusetts Univ. of Chicago
Chicago, IL Irvine, CA Amherst, MA Chicago, IL
umut@tti-c.org ihler@ics.uci.edu mettu@ecs.umass.edu osumer@cs.uchicago.edu
ABSTRACT
Many applications involve repeatedly computing the optimal,
maximum a posteriori (MAP) configuration of a graphical model
as the model changes, often slowly or incrementally over time, e.g.,
due to input from a user. Small changes to the model often require
updating only a small fraction of the MAP configuration, suggest-
ing the possibility of performing updates faster than recomputing
from scratch. In this paper we present an algorithm for efficiently
performing such updates under arbitrary changes to the model. Our
algorithm is within a logarithmic factor of the optimal and is asymp-
totically never slower than re-computing from-scratch: if a modifi-
cation to the model requires m updates to the MAP configuration of
n random variables, then our algorithm requires O(m log (n/m))
time; re-computing from scratch requires O(n) time. We evaluate
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