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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1807) Stochastic gradient descent optimizer for ML library
Date Mon, 04 May 2015 13:07:06 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1807?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14526599#comment-14526599
] 

ASF GitHub Bot commented on FLINK-1807:
---------------------------------------

Github user tillrohrmann commented on a diff in the pull request:

    https://github.com/apache/flink/pull/613#discussion_r29582355
  
    --- Diff: flink-staging/flink-ml/src/test/scala/org/apache/flink/ml/optimization/RegularizationITSuite.scala
---
    @@ -0,0 +1,56 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one
    + * or more contributor license agreements.  See the NOTICE file
    + * distributed with this work for additional information
    + * regarding copyright ownership.  The ASF licenses this file
    + * to you under the Apache License, Version 2.0 (the
    + * "License"); you may not use this file except in compliance
    + * with the License.  You may obtain a copy of the License at
    + *
    + *     http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.flink.ml.optimization
    +
    +import org.apache.flink.ml.common.WeightVector
    +import org.apache.flink.ml.math.DenseVector
    +import org.scalatest.{Matchers, FlatSpec}
    +
    +import org.apache.flink.api.scala._
    +import org.apache.flink.test.util.FlinkTestBase
    +
    +
    +class RegularizationITSuite extends FlatSpec with Matchers with FlinkTestBase {
    +
    +  behavior of "The regularization type implementations"
    +
    +  it should "not change the weights when no regularization is used" in {
    +
    +    val env = ExecutionEnvironment.getExecutionEnvironment
    +
    +    env.setParallelism(2)
    +
    +    val regType = new NoRegularization
    +
    +    val weightVector = new WeightVector(DenseVector(1.0), 1.0)
    +    val effectiveStepsize = 1.0
    +    val regularizationParameter = 0.0
    +    val gradient = DenseVector(0.0)
    +
    +
    +
    --- End diff --
    
    multiple linebreaks


> Stochastic gradient descent optimizer for ML library
> ----------------------------------------------------
>
>                 Key: FLINK-1807
>                 URL: https://issues.apache.org/jira/browse/FLINK-1807
>             Project: Flink
>          Issue Type: Improvement
>          Components: Machine Learning Library
>            Reporter: Till Rohrmann
>            Assignee: Theodore Vasiloudis
>              Labels: ML
>
> Stochastic gradient descent (SGD) is a widely used optimization technique in different
ML algorithms. Thus, it would be helpful to provide a generalized SGD implementation which
can be instantiated with the respective gradient computation. Such a building block would
make the development of future algorithms easier.



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