For functions that have a reasonable structure i.e., 1 or at most a few optima, it is certainly a sensible task. Separable functions are certainly nicer (10K 1D minimizations), but it is pretty easy to devise functions e.g., generalizations of Rosenbrock, Chebyquad and other functions that are high dimension but not separable.
Admittedly, there are not a lot of real-world examples that are publicly available. More would be useful. JN On 02/25/2011 05:06 PM, Bert Gunter wrote: > On Fri, Feb 25, 2011 at 12:00 PM, Brian Tsai <btsa...@gmail.com> wrote: >> Hi John, >> >> Thanks so much for the informative reply! I'm currently trying to optimize >> ~10,000 parameters simultaneously - for some reason, > > -- Some expert (Ravi, John ?) please correct me, but: Is the above not > complete nonsense? I can't imagine poking around usefully in 10K > dimensional space for an extremum unless maybe one can find the > extremum by 10K separate 1-dim optimizations. And maybe not then > either. > > Am I way offbase here, or has Brian merely described just another > inefficient way to produce random numbers? > > -- Bert ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
