Well, that exponential is a Gaussian when q is definite negative (which is often the case). But I see what you mean.
On 10 sept. 2011, at 18:47, Brian Sheppard wrote: > Yes, that makes sense. You don't want Gaussian there. > > -----Original Message----- > From: [email protected] > [mailto:[email protected]] On Behalf Of Rémi Coulom > Sent: Saturday, September 10, 2011 11:36 AM > To: [email protected] > Subject: Re: [Computer-go] CLOP: Confident Local Optimization > forNoisyBlack-Box Parameter Tuning > > > On 10 sept. 2011, at 17:20, Brian Sheppard wrote: > >> I am going through the paper, and there is a point where I do not >> understand. >> >> When the weights are recalculated in Algorithm 1, the expression for >> wk is >> exp((qk(x) - mk) / H * sk). >> >> Should the formula have a square? That is, exp((qk(x) - mk) * (qk(x) - >> mk) / H * sk)? >> >> Thanks, >> Brian > > No. The idea is that the weight of a sample should be low when it is far > below the mean, not when it is far from the mean. That is to say, samples > whose value is very low according to the regression get a low weight. But > samples whose strength is estimated to be above average keep a full weight > of 1 (because of the "min", the weight can never get above 1). > > Note BTW that since my previous message I updated the web site of CLOP with > some data, screenshots, and a link to the computer-chess forum with more > discussions about the algorithm: > http://remi.coulom.free.fr/CLOP/ > > Rémi > _______________________________________________ > 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 _______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
