cool! I will check them out! thanks! Joe On Fri, Sep 2, 2011 at 8:07 AM, Thomas Jungblut < [email protected]> wrote:
> Hi Joe, > > great thank you very much for clarification. > I love classification algorithms, so I'll be very interested in how you > develop this. > "Per se" you can translate every MapReduce algorithm to BSP, since BSP is > an > abstraction to MapReduce. > E.G: Map Phase is a local computation phase, merging and sorting are the > synchronization barrier (needs finish of all map tasks) and reducing is a > computational phase again. > On the english wikipedia is a good schema that shows how the workflow is. > > Actually you can make your map phase as well in BSP, but for the latest > release 0.3.0 you have to write data sharding and partitioning for > yourself. > There are examples and blog posts that shows how code them. > Your reduce step is depending on your implementation. Is there a single > reducer which updates the whole classifier? > > Actually I wanted to implement a k-means clustering in BSP, but sadly I was > very busy and have not too much time for it. It is quite similar to your > algorithm. The Map step is calculating the distance between the current > point and the centers and the reducer is going to update the centers. > > To provide you with a bit of information, I already rewritten an MapReduce > graph algorithm to BSP. [1][2] > These examples are without partitioning, I recently did an improvement to > the partitioning algorithm. So it makes sense to checkout the current trunk > and browse through the graph package and examples package. It contains > improved partitioning as well as graph examples. > > HF and GL. > If you need help, I'll be glad to help you. > > [1] > > http://codingwiththomas.blogspot.com/2011/04/graph-exploration-with-hadoop-mapreduce.html > [2] > > http://codingwiththomas.blogspot.com/2011/04/graph-exploration-using-apache-hama-and.html > > 2011/9/2 Zhiyong Xie <[email protected]> > > > 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 > > > > > > -- > Thomas Jungblut > Berlin > > mobile: 0170-3081070 > > business: [email protected] > private: [email protected] > -- Joe (Zhiyong) Xie Graduate Student Electrical Engineering Department University of Washington, Seattle, WA LinkedIn: http://www.linkedin.com/in/zhiyongxie
