Github user debasish83 commented on the pull request:
https://github.com/apache/spark/pull/3890#issuecomment-98190811
I mean for svm the formulation is over all rows right...the smooth max will
be done on every row and label...max(0, 1 - y_i a_i*x)...so only change will be
a diff function that calculates the logsumexp and gradient of logsumexp from
each data row and we aggregate it on the master and solve using BFGS...as long
as the alpha of logsumexp has been tuned (smooth at first, as we go down,
tighten it) BFGS will converge to a good solution...
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