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

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: GridSoccer Simulator is a multiagent soccer simulator in a gridworld environment. The environment provides a testbed for machinelearning, and control algorithms, especially multiagent reinforcement learning. 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: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more. Changes:New maximum cluster argument for all algorithms. Also no more matlab interface since it seemed no one was using it, and I cannot support it any longer.

About: This program is a 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. The program uses the multinomial event model for representation, the maximum likelihood estimate with a Laplace smoothing technique for learning parameters. A sparsedata structure is defined to represent the feature vector in the program to seek higher computational speed. 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: A Matlab implementation of Uncorrelated Multilinear PCA (UMPCA) for dimensionality reduction of tensor data via tensortovector projection Changes:Initial Announcement on mloss.org.

About: A C++ Library for Discrete Graphical Models Changes:Initial Announcement on mloss.org.
