About: learn optimized scoring systems using MATLAB and the CPLEX Optimization Studio Changes:Initial Announcement on mloss.org.

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. Changes:This release adds support for cuDNN 5.1 as well as a number of minor bug fixes and usability improvements.

About: This is an optimization library based on Social Impact Theory(SITO). The optimizer works in the same way as PSO and GA. Changes:bug removed

About: Python toolbox for manifold optimization with support for automatic differentiation Changes:Initial Announcement on mloss.org.

About: DiffSharp is a functional automatic differentiation (AD) library providing gradients, Hessians, Jacobians, directional derivatives, and matrixfree Hessian and Jacobianvector products as higherorder functions. It allows exact and efficient calculation of derivatives, with support for nesting. Changes:Fixed: Bug fix in forward AD implementation of Sigmoid and ReLU for D, DV, and DM (fixes #16, thank you @mrakgr) Improvement: Performance improvement by removing several more Parallel.For and Array.Parallel.map operations, working better with OpenBLAS multithreading Added: Operations involving incompatible dimensions of DV and DM will now throw exceptions for warning the user

About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinearoptimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python. Changes:Fixed bug in save/restore. Fixed bug in initial design.

About: Hype is a proofofconcept deep learning library, where you can perform optimization on compositional machine learning systems of many components, even when such components themselves internally perform optimization. Changes:Initial Announcement on mloss.org.

About: Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning tasks, both supervised and unsupervised.This package provides several distinct approaches to solve such problems including some helpful facilities such as crossvalidation and a plethora of score functions. Changes:This minor release has the same feature set as Optunity 1.1.0, but incorporates several bug fixes, mostly related to the specification of structured search spaces.

About: SALSA (Software lab for Advanced machine Learning with Stochastic Algorithms) is an implementation of the wellknown stochastic algorithms for Machine Learning developed in the highlevel technical computing language Julia. The SALSA software package is designed to address challenges in sparse linear modelling, linear and nonlinear Support Vector Machines applied to large data samples with usercentric and userfriendly emphasis. Changes:Initial Announcement on mloss.org.

About: R package implementing statistical test and post hoc tests to compare multiple algorithms in multiple problems. Changes:Initial Announcement on mloss.org.

About: This package is an implementation of a linear RankSVM solver with nonconvex regularization. Changes:Initial Announcement on mloss.org.

About: Universal Pythonwritten numerical optimization toolbox. Problems: NLP, LP, QP, NSP, MILP, LSP, LLSP, MMP, GLP, SLE, MOP etc; general logical constraints, categorical variables, automatic differentiation, stochastic programming, interval analysis, many other goodies Changes:http://openopt.org/Changelog

About: DAL is an efficient and flexibible MATLAB toolbox for sparse/lowrank learning/reconstruction based on the dual augmented Lagrangian method. Changes:

About: minFunc is a Matlab function for unconstrained optimization of differentiable realvalued multivariate functions using linesearch methods. It uses an interface very similar to the Matlab Optimization Toolbox function fminunc, and can be called as a replacement for this function. On many problems, minFunc requires fewer function evaluations to converge than fminunc (or minimize.m). Further it can optimize problems with a much larger number of variables (fminunc is restricted to several thousand variables), and uses a line search that is robust to several common function pathologies. Changes:Initial Announcement on mloss.org.

About: [FACTORIE](http://factorie.cs.umass.edu) is a toolkit for deployable probabilistic modeling, implemented as a software library in [Scala](http://scalalang.org). It provides its users with a succinct language for creating [factor graphs](http://en.wikipedia.org/wiki/Factor_graph), estimating parameters and performing inference. It also has implementations of many machine learning tools and a full NLP pipeline. Changes:Initial Announcement on mloss.org.

About: PLEASD: A Matlab Toolbox for Structured Learning Changes:Initial Announcement on mloss.org.

About: The Maja Machine Learning Framework (MMLF) is a general framework for problems in the domain of Reinforcement Learning (RL) written in python. It provides a set of RL related algorithms and a set of benchmark domains. Furthermore it is easily extensible and allows to automate benchmarking of different agents. Changes:

About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others. Changes:

About: PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easytouse yet still powerful algorithms for machine learning tasks, including a variety of predefined [...] Changes:
