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https://issues.apache.org/jira/browse/FLINK-1979?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15286469#comment-15286469
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ASF GitHub Bot commented on FLINK-1979:
---------------------------------------
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1985#discussion_r63509731
--- Diff:
flink-libraries/flink-ml/src/main/scala/org/apache/flink/ml/optimization/LossFunction.scala
---
@@ -23,8 +23,8 @@ import org.apache.flink.ml.math.BLAS
/** Abstract class that implements some of the functionality for common
loss functions
*
- * A loss function determines the loss term $L(w) of the objective
function $f(w) = L(w) +
- * \lambda R(w)$ for prediction tasks, the other being regularization,
$R(w)$.
+ * A loss function determines the loss term `L(w)` of the objective
function `f(w) = L(w) +
+ * lambda*R(w)` for prediction tasks, the other being regularization,
`R(w)`.
--- End diff --
Good catch :-)
> Implement Loss Functions
> ------------------------
>
> Key: FLINK-1979
> URL: https://issues.apache.org/jira/browse/FLINK-1979
> Project: Flink
> Issue Type: Improvement
> Components: Machine Learning Library
> Reporter: Johannes Günther
> Assignee: Johannes Günther
> Priority: Minor
> Labels: ML
>
> For convex optimization problems, optimizer methods like SGD rely on a
> pluggable implementation of a loss function and its first derivative.
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