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From wang...@apache.org
Subject svn commit: r1687421 - /incubator/singa/site/trunk/content/markdown/develop/schedule.md
Date Thu, 25 Jun 2015 07:58:26 GMT
Author: wangwei
Date: Thu Jun 25 07:58:26 2015
New Revision: 1687421

URL: http://svn.apache.org/r1687421
Log:
update schedule

Modified:
    incubator/singa/site/trunk/content/markdown/develop/schedule.md

Modified: incubator/singa/site/trunk/content/markdown/develop/schedule.md
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/content/markdown/develop/schedule.md?rev=1687421&r1=1687420&r2=1687421&view=diff
==============================================================================
--- incubator/singa/site/trunk/content/markdown/develop/schedule.md (original)
+++ incubator/singa/site/trunk/content/markdown/develop/schedule.md Thu Jun 25 07:58:26 2015
@@ -21,13 +21,13 @@ Notice:    Licensed to the Apache Softwa
 | Release | Module| Feature | Status |
 |---------|---------|-------------|--------|
 | 0.1     | Neural Network |1.1. Feed forward neural network, including CNN, MLP | done|
-| -Early July |                |1.2. RBM-like model, including RBM | working|
+| -Early July |                |1.2. RBM-like model, including RBM | testing|
 |         |                |1.3. Recurrent neural network, including standard RNN | working|
 |         | Architecture   |1.4. One worker group on single node (with data partition)| done|
 |         |                |1.5. Multi worker groups on single node using [Shared Memory
Hogwild](http://www.eecs.berkeley.edu/~brecht/papers/hogwildTR.pdf)|testing|
-|         |                |1.6. Distributed Hogwild | working|
-|         |                |1.7. Multi groups across nodes, like [Downpour](http://papers.nips.cc/paper/4687-large-scale-distributed-deep-networks)|working|
-|         |                |1.8  All-Reduce training architecture like [DeepImage](http://arxiv.org/abs/1501.02876)|
working|
+|         |                |1.6. Distributed Hogwild | testing|
+|         |                |1.7. Multi groups across nodes, like [Downpour](http://papers.nips.cc/paper/4687-large-scale-distributed-deep-networks)|testing|
+|         |                |1.8  All-Reduce training architecture like [DeepImage](http://arxiv.org/abs/1501.02876)|
testing|
 |         | Resource Management |1.9. Integration with Mesos | working|
 |         | Failure recovery|1.10. Checkpoint and restore |testing|
 |         | Tools|1.11. Installation with GNU auto tools| done|



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