Update release note (#603)

* update readme in ga_squad

* update readme

* fix typo

* Update README.md

* Update README.md

* Update README.md

* update readme

* update

* fix path

* update reference

* fix bug in config file

* update nni_arch_overview.png

* update

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* add release note

docs/RELEASE.md

@@ -1,3 +1,53 @@
+# Release 0.5.0 - 01/14/2019
+## Major Features
+### New tuner and assessor supports
+  * Support [Metis tuner](./HowToChooseTuner.md#MetisTuner) as a new NNI tuner. Metis algorithm has been proofed to be well performed for **online** hyper-parameter tuning.
+  * Support [ENAS customized tuner](https://github.com/countif/enas_nni), a tuner contributed by github community user, is an algorithm for neural network search, it could learn neural network architecture via reinforcement learning and serve a better performance than NAS.
+  * Support [Curve fitting assessor](./HowToChooseTuner.md#Curvefitting) for early stop policy using learning curve extrapolation. 
+
+### Training Service Ehancement
+* [FrameworkController Training service](./FrameworkControllerMode.md): Support run experiments using frameworkcontroller on kubernetes
+   * FrameworkController is a Controller on kubernetes that is general enough to run (distributed) jobs with various machine learning frameworks, such as tensorflow, pytorch, MXNet.
+   * NNI provides unified and simple specification for job definition.
+   * MNIST example for how to use FrameworkController.
+
+### User Experience improvements
+  * A better trial logging support for NNI experiments in PAI, Kubeflow and FrameworkController mode:
+      * An improved logging architecture to send stdout/stderr of trials to NNI manager via Http post. NNI manager will store trial's stdout/stderr messages in local log file.
+      * Show the link for trial log file on WebUI. 
+  * Support to show final result's all key-value pairs.
+
+### Others
+  * [Weight Sharing](./AdvancedNAS.md): Enable weight sharing for NAS algorithms, currently through NFS.
+
+
+# Release 0.4.1 - 12/14/2018
+## Major Features
+### New tuner supports
+  * Support [network morphism](./HowToChooseTuner.md#NetworkMorphism) as a new tuner
+
+### Training Service improvements
+  * Migrate [Kubeflow training service](https://github.com/Microsoft/nni/blob/master/docs/KubeflowMode.md)'s dependency from kubectl CLI to [Kubernetes API](https://kubernetes.io/docs/concepts/overview/kubernetes-api/) client
+  * [Pytorch-operator](https://github.com/kubeflow/pytorch-operator) support for Kubeflow training service
+  * Improvement on local code files uploading to OpenPAI HDFS
+  * Fixed OpenPAI integration WebUI bug: WebUI doesn't show latest trial job status, which is caused by OpenPAI token expiration
+
+### NNICTL improvements
+  * Show version information both in nnictl and WebUI. You can run **nnictl -v** to show your current installed NNI version
+
+### WebUI improvements
+  * Enable modify concurrency number during experiment
+  * Add feedback link to NNI github 'create issue' page
+  * Enable customize top 10 trials regarding to metric numbers (largest or smallest)
+  * Enable download logs for dispatcher & nnimanager 
+  * Enable automatic scaling of axes for metric number
+  * Update annotation to support displaying real choice in searchspace
+
+## New examples
+  * [FashionMnist](https://github.com/Microsoft/nni/tree/master/examples/trials/network_morphism), work together with network morphism tuner
+  * [Distributed MNIST example](https://github.com/Microsoft/nni/tree/master/examples/trials/mnist-distributed-pytorch) written in PyTorch
+
+
 # Release 0.4 - 12/6/2018
 
 ## Major Features
@@ -101,5 +151,3 @@ Initial release of Neural Network Intelligence (NNI).
 
 ## Known Issues
 [Known Issues in release 0.1.0](https://github.com/Microsoft/nni/labels/nni010knownissues).
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