Update Contribute (#741)

website/docs/Contribute.md

@@ -1,12 +1,12 @@
 # Contributing
 
-This project welcomes (and encourages) all forms of contributions, including but not limited to:
+This project welcomes and encourages all forms of contributions, including but not limited to:
 
 -  Pushing patches.
 -  Code review of pull requests.
 -  Documentation, examples and test cases.
 -  Readability improvement, e.g., improvement on docstr and comments.
--  Community participation in [issues](https://github.com/microsoft/FLAML/issues), [discussions](https://github.com/microsoft/FLAML/discussions), and [gitter](https://gitter.im/FLAMLer/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge).
+-  Community participation in [issues](https://github.com/microsoft/FLAML/issues), [discussions](https://github.com/microsoft/FLAML/discussions), and [discord](https://discord.gg/7ZVfhbTQZ5).
 -  Tutorials, blog posts, talks that promote the project.
 -  Sharing application scenarios and/or related research.
 
@@ -26,6 +26,31 @@ This project has adopted the [Microsoft Open Source Code of Conduct](https://ope
 For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
 contact [[email protected]](mailto:[email protected]) with any additional questions or comments.
 
+## How to make a good bug report
+
+When you submit an issue to [GitHub](https://github.com/microsoft/FLAML/issues), please do your best to
+follow these guidelines! This will make it a lot easier to provide you with good
+feedback:
+
+- The ideal bug report contains a short reproducible code snippet. This way
+  anyone can try to reproduce the bug easily (see [this](https://stackoverflow.com/help/mcve) for more details). If your snippet is
+  longer than around 50 lines, please link to a [gist](https://gist.github.com) or a GitHub repo.
+
+- If an exception is raised, please **provide the full traceback**.
+
+- Please include your **operating system type and version number**, as well as
+  your **Python, flaml, scikit-learn versions**. The version of flaml
+  can be found by running the following code snippet:
+```python
+import flaml
+print(flaml.__version__)
+```
+
+- Please ensure all **code snippets and error messages are formatted in
+  appropriate code blocks**.  See [Creating and highlighting code blocks](https://help.github.com/articles/creating-and-highlighting-code-blocks)
+  for more details.
+
+
 ## Becoming a Reviewer
 
 There is currently no formal reviewer solicitation process. Current reviewers identify reviewers from active contributors. If you are willing to become a reviewer, you are welcome to let us know on gitter.
@@ -68,7 +93,6 @@ coverage run -m pytest test
 
 Then you can see the coverage report by
 `coverage report -m` or `coverage html`.
-If all the tests are passed, please also test run [notebook/automl_classification](https://github.com/microsoft/FLAML/blob/main/notebook/automl_classification.ipynb) to make sure your commit does not break the notebook example.
 
 ### Documentation
 
@@ -91,3 +115,6 @@ yarn start
 
 The last command starts a local development server and opens up a browser window.
 Most changes are reflected live without having to restart the server.
+
+Note:
+some tips in this guide are based off the contributor guide from [ray](https://docs.ray.io/en/latest/ray-contribute/getting-involved.html), [scikit-learn](https://scikit-learn.org/stable/developers/contributing.html), or [hummingbird](https://github.com/microsoft/hummingbird/blob/main/CONTRIBUTING.md).

website/docs/Getting-Started.md

@@ -95,3 +95,5 @@ Then, you can use it just like you use the original `LGMBClassifier`. Your other
 * Refer to [SDK](reference/automl) and [FAQ](FAQ).
 
 If you like our project, please give it a [star](https://github.com/microsoft/FLAML/stargazers) on GitHub. If you are interested in contributing, please read [Contributor's Guide](Contribute).
+
+<iframe src="https://ghbtns.com/github-btn.html?user=microsoft&amp;repo=FLAML&amp;type=star&amp;count=true&amp;size=large" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>

website/docs/Research.md

@@ -1,4 +1,4 @@
-# Research in FLAML
+# Research
 
 For technical details, please check our research publications.
 
@@ -17,7 +17,5 @@ For technical details, please check our research publications.
 * [Economical Hyperparameter Optimization With Blended Search Strategy](https://www.microsoft.com/en-us/research/publication/economical-hyperparameter-optimization-with-blended-search-strategy/). Chi Wang, Qingyun Wu, Silu Huang, Amin Saied. ICLR 2021.
 * [An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models](https://aclanthology.org/2021.acl-long.178.pdf). Susan Xueqing Liu, Chi Wang. ACL 2021.
 * [ChaCha for Online AutoML](https://www.microsoft.com/en-us/research/publication/chacha-for-online-automl/). Qingyun Wu, Chi Wang, John Langford, Paul Mineiro and Marco Rossi. ICML 2021.
-* [Fair AutoML](https://arxiv.org/abs/2111.06495). Qingyun Wu, Chi Wang. ArXiv preprint arXiv:2111.06495 (2021). 
+* [Fair AutoML](https://arxiv.org/abs/2111.06495). Qingyun Wu, Chi Wang. ArXiv preprint arXiv:2111.06495 (2021).
 * [Mining Robust Default Configurations for Resource-constrained AutoML](https://arxiv.org/abs/2202.09927). Moe Kayali, Chi Wang. ArXiv preprint arXiv:2202.09927 (2022).
-
-Many researchers and engineers have contributed to the technology development. In alphabetical order: Vijay Aski, Sebastien Bubeck, Surajit Chaudhuri, Kevin Chen, Yi Wei Chen, Nadiia Chepurko, Ofer Dekel, Alex Deng, Anshuman Dutt, Nicolo Fusi, Jianfeng Gao, Johannes Gehrke, Niklas Gustafsson, Silu Huang, Moe Kayali, Dongwoo Kim, Christian Konig, John Langford, Menghao Li, Mingqin Li, Susan Xueqing Liu, Zhe Liu, Naveen Gaur, Paul Mineiro, Vivek Narasayya, Jake Radzikowski, Marco Rossi, Amin Saied, Neil Tenenholtz, Olga Vrousgou, Chi Wang, Yue Wang, Markus Weimer, Qingyun Wu, Qiufeng Yin, Haozhe Zhang, Minjia Zhang, XiaoYun Zhang, Eric Zhu, Rui Zhuang.