Several Bayes net structure learning algorithms work incrementally by
testing the addition of a single link to a current model , seeing if
it improves some score, such as marginal likelihood, and then
selecting the link which increases the score the most. I remember that
there were some papers a few years back pointing out that this
single-link look-ahead search fails for some special situations and
the simultaneous addition of two links should be considered instead,
but I cannot recall any details of the papers.
I would be grateful if anyone can provide references to papers which
deal with this issue.
Thanks in advance.
Robert Cowell
Department of Actuarial Science and Statistics
City University
Northampton Square
London EC1V 0HB
tel: (44) 020 7477 - 8454
fax (44) 020 7477 - 8838
www: http://www.staff.city.ac.uk/~rgc
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