Thank you Thomas! In short, SVM ( http://en.wikipedia.org/wiki/Support_vector_machine) is a supervised learning classifier described as optimization problem and solved by gradient descent approach (http://en.wikipedia.org/wiki/Stochastic_gradient_descent). It is a iterative process, and kinda run a map/reduce pair per iteration. Map to calculate the gradient value for each point, and reduce phase to optimize the classifier. BSP model seems native for scientific and graph processing in my mind, not figure out or find much info online for this type of application so far .
Best, Joe On Thu, Sep 1, 2011 at 10:36 AM, Thomas Jungblut < [email protected]> wrote: > Hi Joe, > > for non-insiders, would you please clarify what SGD and SVM are? > Then we could give you some tips how to implement them in BSP. > > Greetz, > Thomas > > 2011/9/1 Zhiyong Xie <[email protected]> > > > Hi there, > > > > May I ask whether anyone else have look into the SGD mapping on BSP model > > too? I'm investigating whether BSP model is a good candidate for > > implementing distributed version of SVM SGD. > > > > Thanks! > > Joe > > -- > > Joe (Zhiyong) Xie > > Graduate Student > > > > > > -- > Thomas Jungblut > Berlin > > mobile: 0170-3081070 > > business: [email protected] > private: [email protected] > -- Joe (Zhiyong) Xie Graduate Student
