Github user debasish83 commented on the issue:
https://github.com/apache/spark/pull/14473
ADMM is already available as a breeze solver (BFGS, OWLQN,
NonlinearMinimizer) which is integrated with ml/mllib...It will be great if you
can look into it and let me know if you need pointers in
Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/14473
I'd recommend (a) generate some data; and/or (b) take a look at some larger
public datasets (or samples thereof) such as Criteo
(https://www.kaggle.com/c/criteo-display-ad-challenge/data) or Avito
(
Github user ZunwenYou commented on the issue:
https://github.com/apache/spark/pull/14473
@MLnick You are right. We have apply ADMM to Sparse Logistic Regression
with L1 norm in some CTR applications, the data sets of these applications
almost consist of 10 million dimension and 100 m
Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/14473
@ZunwenYou sorry if I was not clear on the JIRA. I said there that this
should probably be done as a Spark package external to the core initially. That
way you can gather some user feedback and perfo
Github user sethah commented on the issue:
https://github.com/apache/spark/pull/14473
@ZunwenYou Would you mind addressing the comments in the JIRA first? Adding
a new optimization algorithm to an API that is now deprecated definitely
warrants more high level discussion before code re
Github user ZunwenYou commented on the issue:
https://github.com/apache/spark/pull/14473
@MLnick please have a look at this.
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