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About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive. Changes:Incremental update, fixing some cosmetic issues, coincides with JMLR publication.

About: Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices. Changes:Initial Announcement on mloss.org.

About: redsvd is a library for solving several matrix decomposition (SVD, PCA, eigen value decomposition) redsvd can handle very large matrix efficiently, and optimized for a truncated SVD of sparse matrices. For example, redsvd can compute a truncated SVD with top 20 singular values for a 100K x 100K matrix with 10M nonzero entries in about two second. Changes:Initial Announcement on mloss.org.

About: The gmm toolbox contains code for density estimation using mixtures of Gaussians: Starting from simple kernel density estimation with spherical and diagonal Gaussian kernels over manifold Parzen window until mixtures of penalised full Gaussians with only a few components. The toolbox covers many Gaussian mixture model parametrisations from the recent literature. Most prominently, the package contains code to use the Gaussian Process Latent Variable Model for density estimation. Most of the code is written in Matlab 7.x including some MEX files. Changes:Initial Announcement on mloss.org

About: A collection of clustering algorithms implemented in Javascript. Changes:Initial Announcement on mloss.org.

About: A stochastic variant of the mirror descent algorithm employing Langford and Zhang's truncated gradient idea to minimize L1 regularized loss minimization problems for classification and regression. Changes:Fixed major bug in implementation. The components of the iterate where the current example vector is zero were not being updated correctly. Thanks to Jonathan Chang for pointing out the error to us.

About: Feature Selection SVM using penalty functions Changes:Fetched by rcranrobot on 20130401 00:00:07.509844

About: An implementation of the infinite hidden Markov model. Changes:Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.

About: BCPy2000 provides a platform for rapid, flexible development of experimental BrainComputer Interface systems based on the BCI2000.org project. From the developer's point of view, the implementation [...] Changes:Bugfixes and tuneups, and an expanded set of (some more, some lessdocumented, optional tools)

About: The library implements Optimized Cutting Plane Algorithm (OCAS) for efficient training of linear SVM classifiers from largescale data. Changes:Implemented COFFIN framework which allows efficient training of invariant image classifiers via virtual examples.
