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About: The Multiagent decision process (MADP) Toolbox is a free C++ software toolbox for scientific research in decisiontheoretic planning and learning in multiagent systems. Changes:Includes freshly written spirit parser for .pomdp files. Includes new code for pruning POMDP vectors; obviates dependence on Cassandra's code and old LP solve version. Includes new factor graph solution code Generalized firefighting CGBG domain added Simulation class for Factored DecPOMDPs and TOI DecMDPs Approximate BG clustering methods and kGMAA with clustering.

About: A MATLAB toolkit for performing generalized regression with equality/inequality constraints on the function value/gradient. Changes:Initial Announcement on mloss.org.

About: Regularization paTH for LASSO problem (thalasso) thalasso solves problems of the following form: minimize 1/2X*betay^2 + lambda*sumbeta_i, where X and y are problem data and beta and lambda are variables. Changes:Initial Announcement on mloss.org.

About: Easily prototype WEKA classifiers and filters using Python scripts. Changes:0.3.0
0.2.1
0.2.0
0.1.1
0.1.0

About: SAMOA is a platform for mining big data streams. It is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms. Changes:Initial Announcement on mloss.org.

About: LDPar is an efficient datadriven dependency parser. You can train your own parsing model on treebank data and parse new data using the induced model. Changes:Initial Announcement on mloss.org.

About: This program is a C++ implementation of Linear Discriminant Function Classifier. Discriminant functions such as perceptron criterion, cross entropy (CE) criterion, and least mean square (LMS) criterion (all for multiclass classification problems) are supported in it. The program uses a sparsedata structure to represent the feature vector to seek higher computational speed. Some other techniques such as online updating, weights averaging, gaussian prior regularization are also supported. Changes:Initial Announcement on mloss.org.

About: CURFIL uses NVIDIA CUDA to accelerate random forest training and prediction for RGB and RGBD images. It focuses on image labelling tasks, such as image segmentation or classification applications. CURFIL allows to search for optimal hyperparameter configurations (e.g. using the hyperopt) package) by massively decreasing training time. Changes:Initial Announcement on mloss.org.

About: This is an unoptimized implementation of the RFD binary descriptor, which is published in the following paper. B. Fan, et al. Receptive Fields Selection for Binary Feature Description. IEEE Transaction on Image Processing, 2014. doi: http://dx.doi.org/10.1109/TIP.2014.2317981 Changes:Initial Announcement on mloss.org.
