I have no idea. I did not really spend any time trying to prove mathematically that CLOP works. Another source of ideas might be that paper about a similar method, where they propose a proof of convergence: http://www.informs-sim.org/wsc07papers/041.pdf But the algorithm is extremely complicated, and I did not understand that proof (they don't give details, only theorems). I wonder how they can have theorems that have no probabilities or expectations in them, when they have noisy measurements. I expect any convergence proof should be a proof of stochastic convergence (ie, almost sure, with probability one, ...).
Rémi On 9 nov. 2011, at 01:34, Brian Sheppard wrote: > Is it possible that convergence properties of CLOP can be established by > relating it to Boosted Regression? > > The successive exponential weights remind me of boosting... > > Brian > > _______________________________________________ > Computer-go mailing list > [email protected] > http://dvandva.org/cgi-bin/mailman/listinfo/computer-go _______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
