Hello there, Tonight I finally finished one part of a really long odyssey to streamline mlpack's release process. The release process used to have about 20 steps involved and would take me an evening. But after the website revamp, it has been significantly simplified and automated, and basically all I had to do was write a script to do the release for me, like we do with ensmallen. So, all that said, I present mlpack 3.1.0:
http://www.mlpack.org/files/mlpack-3.1.0.tar.gz Here's the changelog (it's pretty long): * Add DiagonalGaussianDistribution and DiagonalGMM classes to speed up the diagonal covariance computation and deprecate DiagonalConstraint (#1666). * Add kernel density estimation (KDE) implementation with bindings to other languages (#1301). * Where relevant, all models with a `Train()` method now return a `double` value representing the goodness of fit (i.e. final objective value, error, etc.) (#1678). * Add implementation for linear support vector machine (see `src/mlpack/methods/linear_svm`). * Change DBSCAN to use PointSelectionPolicy and add OrderedPointSelection (#1625). * Residual block support (#1594). * Bidirectional RNN (#1626). * Dice loss layer (#1674, #1714) and hard sigmoid layer (#1776). * `output` option changed to `predictions` and `output_probabilities` to `probabilities` for Naive Bayes binding (`mlpack_nbc`/`nbc()`). Old options are now deprecated and will be preserved until mlpack 4.0.0 (#1616). * Add support for Diagonal GMMs to HMM code (#1658, #1666). This can provide large speedup when a diagonal GMM is acceptable as an emission probability distribution. * Python binding improvements: check parameter type (#1717), avoid copying Pandas dataframes (#1711), handle Pandas Series objects (#1700). This release contains basically all the improvements that I mentioned in the slides of the mlpack video meeting: http://www.ratml.org/misc/mlpack-meeting-slides.pdf The only things that are in master but not in 3.1.0 are the GAN support, which is not quite ready yet, and the MVU code (which honestly should just be removed since it never worked...). Like I mentioned there, we've merged over 65 pull requests this year alone (probably closer to 70 now) and many of these are by new contributors. The code in this release absolutely would not have been possible without everyone's contributions. So, thanks to everyone! I am really excited about future directions. Usually, I mention something at the end of these release emails about things to look forward to in future releases, but mostly we figured that out and set out some directions in the video meeting and follow-up emails. So instead the 'thing to look forward to' would be more regular releases---now that this process has become somewhat streamlined, it's really easy. If you find any bugs or issues, please feel free to report on Github or in IRC. More information on how to get in touch can be found at http://mlpack.org/community.html. I hope everyone has a great day! This process has kept me up a bit later than I hoped so I am going to bed now... :) Ryan -- Ryan Curtin | "It's too bad she won't live! But then again, who [email protected] | does?" - Gaff _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
