John, There has been no rigorous testing yet. My primary concern in the averaging algorithm is process latency, completion time, and faults. Do you have specifics you would like to share?
_Chris On Mon, Jun 9, 2014 at 11:24 AM, John Myles White <[email protected]> wrote: > Very cool, Chris. > > I’ve done a lot of work on SGD in Julia, so I’m glad to see more. > > Regarding the averaging technique you’re using, have you done much testing > to see how well it works? My sense is that the algorithm you’re using is a > little brittle, but perhaps I’ve misunderstood it. > > — John > > On Jun 8, 2014, at 11:36 AM, Christopher Fusting <[email protected]> > wrote: > > Hi everyone. I've been playing around with Julia for awhile now and have > implemented Parallel Stochastic Gradient Descent. This is my first Julia > project (and attempt at implementing this algorithm) so its not perfect, > but I think I have a good start and wanted to share it: > https://github.com/cfusting/PSGD.jl. I welcome any feedback. > > Eventually I'd like to integrate the package with DataFrames and do a > little optimization, especially on the algorithm that partition the data. > > _Chris > > > -- Christopher W. Fusting *Software Developer / Analyst* @cfusting 828-772-0012
