[mlpack] GSoC 2018 is finished!

[Ryan Curtin]

Hello everyone,

It's been a great summer and we're finally at the end of it.  Earlier
this week, the results from Google Summer of Code were announced, and
I'm happy to report that all six of our students this year passed (all
with flying colors of course!).  Here's a quick summary and status of
each project:

Yasmine Dumouchel (mentored by me):

  Go bindings are being automatically generated successfully and they
  are tested; there are just a handful more things to work out before
  merging it into mlpack entirely, then mlpack can be used from Go!

Wenhao Huang (mentored by Mikhail Lozhnikov):

  The CF (collaborative filtering) module gains the ability to remove
  global effects and to use weighted sums for the rating calculation.
  Moreover some decomposition techniques like SVD++ and Bias SVD will be
  merged soon after some final checks.

Shikhar Jaiswal (mentored by Marcus Edel):

  Several Generative adversarial networks (GAN, DCGAN and WGAN) are
  implemented; the GAN implementation is almost 1.5 times faster than a
  comparable Tensorflow implementation (CPU); on top of that, restricted
  Boltzmann machines (RBM's) were implemented including several
  optimizations for the network code.

Atharva Khandait (mentored by Sumedh Ghaisas):

  Multilayer perceptron and convolutional VAE's (Variational
  Autoencoder) were implemented, in addition to a reconstruction of the
  existing loss computation structure and several optimizations and
  fixes (Sequence layer, Gradient calculation to name a few) for the
  network code; some bits are still being optimized and should be merged
  in the future.

Manish Kumar (mentored by me):

  Both LMNN and BoostMetric (distance learning techniques) are
  implemented; LMNN is very fast and still being optimized further, and
  BoostMetric should be merged in the future).

Haritha Nair (mentored by Marcus Edel):

  The neural collaborative filtering (NCF) framework was implemented;
  besides introducing the policy design pattern into the existing CF
  framework, there are some issues we have to work out before we can
  entirely merge all additions and modifications.

Each of these projects was a great effort, and I'm really excited about
seeing these features become parts of subsequent mlpack releases.  Thank
you to everyone who participated in this program, including all of the
students who applied and contributed during the application process, all
of the mentors who helped out, and all of the students who were accepted
and did great work on their projects.

We'll be releasing mlpack 3.1.0 shortly, which will include the code
generated from these projects. :)

Have a great weekend!

-- 
Ryan Curtin    | "If it's something that can be stopped, then just try to stop it!"
ryan at ratml.org |   - Skull Kid