[Incubator Wiki] Update of "November2016" by DeronEriksson

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The "November2016" page has been changed by DeronEriksson:
https://wiki.apache.org/incubator/November2016?action=diff&rev1=26&rev2=27

Comment:
SystemML status update for November 2016

  SystemML provides declarative large-scale machine learning (ML) that aims at
  flexible specification of ML algorithms and automatic generation of hybrid
  runtime plans ranging from single node, in-memory computations, to distributed
- computations such as Apache Hadoop MapReduce and Apache Spark.
+ computations running on Apache Hadoop MapReduce and Apache Spark.
  
  SystemML has been incubating since 2015-11-02.
  
  Three most important issues to address in the move towards graduation:
  
-   1.
-   2.
-   3.
+  - Grow SystemML community: increase mailing list activity,
+    increase adoption of SystemML for scalable machine learning, encourage
+    data scientists to adopt DML and PyDML algorithm scripts, respond to
+    user feedback to ensure SystemML meets the requirements of real-world
+    situations, write papers, and present talks about SystemML.
+  - Continue to produce releases.
+  - Increase the diversity of our project's contributors and committers.
  
- Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
+ Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware
- aware of?
+ of?
  
+  NONE.
  
- 
- How has the community developed since the last report?
- 
- 
- 
- How has the project developed since the last report?
+ How has the community developed since the last report?
+  Our mailing list from August through October had 375 messages on a wide range
+  of topics. We have gained 4 new contributors to the main project since August
+  1st. Our website has been redesigned with the help of several design engineers
+  and we have commits from 3 new contributors to the website project. On GitHub,
+  the project has been starred 417 times and forked 156 times.
  
+  Niketan Pansare gave a talk with the title "Apache SystemML - Declarative
+  Machine Learning at Scale" on October 7th in the CS graduate seminar at UC
+  Merced. Matthias Boehm gave a talk on "Compressed Linear Algebra for Large-
+  Scale Machine Learning" at TU Dresden on August 30th. We presented the papers
+  "Compressed Linear Algebra for Large-Scale Machine Learning" (research paper +
+  poster) and "SystemML: Declarative Machine Learning on Spark" (industry paper)
+  at VLDB'16. The "Compressed Linear Algebra for Large-Scale Machine Learning"
+  paper won the VLDB 2016 Best Paper Award. We gave two 90 minute tutorials at the
+  BOSS'16 workshop, co-located with VLDB'16, and our paper "SPOOF: Sum-Product
+  Optimization and Operator Fusion for Large-Scale Machine Learning" has been
+  accepted at CIDR'17.
  
+ How has the project developed since the last report?
+  The main project has had 213 commits since August 1. The website project has
+  had 51 commits since August 1. Since August 1, 241 issues have been reported
+  on our JIRA site and 137 issues have been resolved or closed. 79 pull requests
+  have been created since August 1, and 72 pull requests have been closed.
  
  Date of last release:
  
-   XXXX-XX-XX
+  2016-06-15 (version 0.10.0-incubating)
  
  When were the last committers or PMC members elected?
  
- 
+  2016-05-07 Glenn Weidner
+  2016-05-07 Faraz Makari Manshadi
  
  Signed-off-by:
  

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