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Adaptive updates for MAP configurations with applications to bioinformatics
2009 IEEE/SP 15th Workshop on Statistical Signal Processing
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, suggesting the possibility of performing updates faster than recomputing from scratch. In this paper we present an algorithm for efficiently performing such updates under arbitrarydoi:10.1109/ssp.2009.5278552 fatcat:wb4i4pbwdrai3psjzwuipabp4y