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[D] r/MachineLearning's 2016 Best Paper Award!

Hi guys!

Welcome to /r/MachineLearning's 2016 Best Paper Award!

The idea is to have a community-wide vote for the best papers of this year.

I hope you find this to be a good idea, mods please tell me if this breaks any rules/if you had something like this in store.

---

## How does it work?

**Nominate** by commenting on the dedicatd top level comments. Please provide a (paywall free) link. Feel free to justify your choice. Also if you're one of the author, be courteous and indicate it.

**Vote** by upvoting the nominees.

The **results** will be announced **by the end of next week** (6-7th of Jan.). Depending on the participation/interest I might change it.

It's that simple!

There are some simple rules to make sure everything runs smoothly, you can find them below, please read them before commenting.

---

## Categories

- [Best Paper of the year](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrapti/)

> No rules! Any research paper you feel had the greatest impact/had top writing, any criterion is good.

- [Best student paper](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbraqkv/)

> Papers from a student, grad/undergrad/highschool, everyone who doesn't have a phd and goes to school. The student must be first author of course. Provide evidence if possible.

- [Best paper name](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrar08/)

> Try to beat [this](http://www.oneweirdkerneltrick.com/spectral.pdf)

- [Best paper from academia](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbraroz/)

> Papers where the first author is from a university / a state research organization (eg INRIA in France).

- [Best paper from the industry](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrasnz/)

> Great paper from a multi-billion tech company (or more generally a research lab sponsored by privat funds, eg. openai)

- [Best rejected paper](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrat9t/)

> A chance of redemption for good papers that didn't make it trough peer review. Please provide evidence that the paper was rejected if possible.

- [Best unpublished preprint](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbratyb/)

> A category for those yet to be published (e.g. papers from the end of the year). This may or may not be redundant with the rejected paper category, we'll see.

- [Best theoretical paper](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrauan/)

> Keep the math coming

- [Best non Deep Learning paper](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbraumv/)

> Because gaussian processes, random forests and kernel methods deserve a chance amid the DL hype train

---

## Rules

1. Only one nomination by comment. You can nominate multiple papers in different comments/categories.
2. Nominations should include a **link to the paper**. In case of an arxiv link, please link to the arxiv page and not the pdf directly. Please do not link paywalled articles.
3. Only **research paper** are to be nominated. This means no book, no memo or no tutorial/blog post for instance. This could be adressed in a separate award or category if there is enough demand.
4. For the sake of clarity, there are some rules on commenting :
- ***Do NOT comment on the main thread***. For discussion, use the [*discussion* thread](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrap6u/)
- ***Please ONLY comment the other threads with nominations***. You can discuss individual nominations in child comments. However 1rst level comments on each thread should be nominations only.
Using Python 3.6 in Ubuntu 16.04 - Anaconda way

### Notice:
This requires starting a virtual environment whenever you wish to use Python 3.6. However this does solve the f string highlighting issue that comes with using pip.

### Installation Instructions:

Download [Full Anaconda](https://www.continuum.io/downloads#linux) (Python 3.5 version)

Install Anaconda

bash Anaconda3-4.2.0-Linux-x86_64.sh
conda update conda

Create a virtual environment with Python 3.6

conda create --name snowflakes python=3.6
source activate snowflakes

Install a python3.6 kernel in Jupyter

python3.6 -m pip install ipykernel
python3.6 -m ipykernel install --user

### Note:
How this is different from the pip installation instructions is that you will end up with version 4.2.3 of the notebook server using Anaconda and version 4.2.1 using pip. This update fixes the f string formatting issue.

### Using the Jupyter Notebook:
Unlike when installing with pip, if you use Anaconda, you will need to have an active virtual environment within a terminal to use Python 3.6.

I use `jupyter notebook --no-browser` so that I can choose the browser I run the notebook in, so I use the following commands in the terminal.

source activate snowflakes
jupyter notebook --no-browser

When I'm done ctrl-C twice to close the notebook and `source deactivate snowflake` exit the virtual environment.

/r/IPython
https://redd.it/5l0ai7
Why is always a with statement needed for working with files?

I have a very basic query about python. I've seen most examples use the `with` statement to read from or write to a file, something like this:

with open('output.txt','w') as f:
f.write(html_doc)

Is it not a better idea to simply call `open('output.txt','w').write(html_doc)` considering simplicity is very much preferred in python? Is closing file handles absolutely necessary, because similar i/o functions in `php` don't require you to close the file handles.

/r/Python
https://redd.it/5l2ld9
What special features or batteries does Django ship with that Flask doesn't has?

I've always used only flask for all the web apps I've built and surprisingly, I've never needed something like django. For database interaction, I always had `sqlalchemy`, for other stuff like the google api client library or something, I usually just `pip install` stuff that I need.

As a result, I've never felt the need to look much deeper into something like django. Nevertheless, since django is so much popular than flask and everyone seem to sing praises of it, I'm curious to know what all batteries are included in it that makes it more "fully featured" as a lot of developers say, when compared to flask.

/r/Python
https://redd.it/5l353d
Python function output into a django model

I am fairly new to django, and am having some trouble getting the output from a function into a model where it will be stored.

The idea is that the list of list function output is a name and a id string, and will be stored as values in the db with the default auto generated primary key.

[['t5.lg.ubuntu.template', '2c91808656b597ff0156ba98b79901f9'], ['DigitalOcean Ubuntu 14.04 Large FRA', '4028818650d4aca10150d4bf63470003'], ['DigitalOcean Ubuntu 14.04 Large NYC2', '4028818650d4aca10150d4bf63470004'], ['DigitalOcean Ubuntu 14.04 XLarge LON', '4028818650d4aca10150d4bf63470005']]

The functionality that i am looking for are fields in the database that I can periodically update by calling the function with any new values and updating the model.

This is my model that I currently have.

class dchqServerBlueprints(models.Model):
blueprintName = models.CharField(max_length=255)
blueprintId = models.CharField(max_length=255)

def __str__(self):
return (self.blueprintId, self.blueprintName)

After a lot of googling, I am pretty stuck on how to go about this. I've seen some references to serializing a list into JSON and storing that JSON in the database, but that seems a little excessive.
Any pointers on how to approach this problem would be greatly appreciated.

/r/django
https://redd.it/5l2a2v
Is there a Markdown alternative to sphinx-apidoc for autogenerating documentation from source?

While I appreciate the functionality of sphinx, I really think that Markdown is a better plaintext format than Restructured Text, so I've been writing documentation using [mkdocs](http://www.mkdocs.org/), which works really well for guides etc.

However, when it comes to generating API documentation from docstrings, there don't seem to be many options that support Markdown or straight-to-HTML. One option is [pdoc](http://pdoc.burntsushi.net/pdoc), which works very well but doesn't support structured docstrings in any of Sphinx, Google, or Numpy style.

Does anyone know of a better option for such a purpose?

/r/Python
https://redd.it/5l6r7v
Did Python Earn You Any Passive Income in 2016?

Inspired by this post from [HackerNews](https://news.ycombinator.com/item?id=13150144).

Did you automate, create, or somehow leverage python for any side hustle this year?

/r/Python
https://redd.it/5l7wgc