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Xiangrui Meng commented on SPARK-1503: -------------------------------------- [~staple] Thanks for picking up this JIRA! TFOCS is a good place to start. We can support AT (Auslender and Teboulle) update, line search, and restart in the first version. It would be nice to take generic composite objective functions. Please note that this could become a big task. We definitely need to go through the design first. > Implement Nesterov's accelerated first-order method > --------------------------------------------------- > > Key: SPARK-1503 > URL: https://issues.apache.org/jira/browse/SPARK-1503 > Project: Spark > Issue Type: New Feature > Components: MLlib > Reporter: Xiangrui Meng > > Nesterov's accelerated first-order method is a drop-in replacement for > steepest descent but it converges much faster. We should implement this > method and compare its performance with existing algorithms, including SGD > and L-BFGS. > TFOCS (http://cvxr.com/tfocs/) is a reference implementation of Nesterov's > method and its variants on composite objectives. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org