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About: You should never compute, maintain, or update the inverse of a symmetric positive definite matrix if you do not have to. Computing the inverse or manipulating it is inherently instable. You can [...] Changes:Initial Announcement on mloss.org.

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: The Computational Infrastructure for Operations Research (COINOR) project is an initiative to spur the development of opensource software for the operations research community. Changes:Initial Announcement on mloss.org.

About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the wellknown SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation. Changes:Initial Announcement on mloss.org.

About: Fast Multidimensional GP Inference using Projected Additive Approximation Changes:Initial Announcement on mloss.org.

About: We study the problem of robust feature extraction based on L21 regularized correntropy in both theoretical and algorithmic manner. In theoretical part, we point out that an L21norm minimization can be justified from the viewpoint of halfquadratic (HQ) optimization, which facilitates convergence study and algorithmic development. In particular, a general formulation is accordingly proposed to unify L1norm and L21norm minimization within a common framework. In algorithmic part, we propose an L21 regularized correntropy algorithm to extract informative features meanwhile to remove outliers from training data. A new alternate minimization algorithm is also developed to optimize the nonconvex correntropy objective. In terms of face recognition, we apply the proposed method to obtain an appearancebased model, called SparseFisherfaces. Extensive experiments show that our method can select robust and sparse features, and outperforms several stateoftheart subspace methods on largescale and open face recognition datasets. Changes:Initial Announcement on mloss.org. 
About: Feature Selection SVM using penalty functions Changes:Fetched by rcranrobot on 20130401 00:00:07.509844

About: Relevant Dimension Estimation (RDE) in Feature Spaces: The package provides functions for estimating the relevant dimension of a data set in feature spaces, applications to model selection, [...] Changes:Initial Announcement on mloss.org.

About: OpenPRNBEM is an C++ implementation of Naive Bayes Classifier, which is a wellknown generative classification algorithm for the application such as text classification. The Naive Bayes algorithm requires the probabilistic distribution to be discrete. OpenPRNBEM uses the multinomial event model for representation. The maximum likelihood estimate is used for supervised learning, and the expectationmaximization estimate is used for semisupervised and unsupervised learning. Changes:Initial Announcement on mloss.org.

About: BudgetedSVM is an opensource C++ toolbox for scalable nonlinear classification. The toolbox can be seen as a missing link between LibLinear and LibSVM, combining the efficiency of linear with the accuracy of kernel SVM. We provide an Application Programming Interface for efficient training and testing of nonlinear classifiers, supported by data structures designed for handling data which cannot fit in memory. We also provide commandline and Matlab interfaces, providing users with an efficient, easytouse tool for largescale nonlinear classification. Changes:Changed license from LGPL v3 to Modified BSD.
