Thank you, Olivier. Let the observable function value be o(x). It can be defined as:
o(x) = 1, with probability f(x); o(x) = 0, with probability (1 - f(x)). where f(x) = 1 / (1 + e(-r(x))) has been defined in the paper. Also, we can see that the expected value is f(x). Did I get this correct? Best regards, Chin-Chang Yang, 2013/03/06 2013/3/6 Olivier Teytaud <[email protected]> > It's a Bernoulli noise. > define f (x) = 1/ (1 + e(−r(x)) ) > and the objective function at x is 1 with probability f(x). > So the expected value at x is f(x), but the values you get are noisy. > > Best regards, > Olivier > > >> Since the functions are not noise-free, they should be defined in terms >>> of some noise. I really need the definition of the noise for comparison >>> between CLOP and other optimizers. >>> >>> I have downloaded the source codes, but I cannot find the codes related >>> to the noise currently. >>> >>> > _______________________________________________ > Computer-go mailing list > [email protected] > http://dvandva.org/cgi-bin/mailman/listinfo/computer-go > -- Chin-Chang Yang
_______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
