Github user dbtsai commented on the pull request:
https://github.com/apache/spark/pull/8013#issuecomment-136545956
Hello, robust tuning parameter k should not be a constant as you
implemented.
In the paper,
http://users.stat.umn.edu/~sandy/courses/8053/handouts/robust.pdf
`k = 1.345Ï` where `Ï` is the square error of current weight. But this
will be very expensive to compute the current square error of weight and then
compute the huber loss, so I think it's reasonable to approximate the square
error from previous weight.
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