Showing Items 401-420 of 676 on page 21 of 34: First Previous 16 17 18 19 20 21 22 23 24 25 26 Next Last
About: This software is an implementation of Hidden Markov Support Vector Machines (HMSVMs). Changes:Initial Announcement on mloss.org.
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About: ClowdFlows is a web based platform for service oriented data mining publicly available at http://clowdflows.org . A web based interface allows users to construct data mining workflows that are hosted on the web and can be (if allowed by the author) accessed by anyone by following a URL of the workflow. Changes:Initial Announcement on mloss.org.
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About: A probabilistic programming language embedded in Haskell. Changes:Initial Announcement on mloss.org.
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About: Multi-class vector classification based on cost function-driven learning vector quantization , minimizing misclassification. Changes:Initial Announcement on mloss.org.
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About: Hyperstream is a large-scale, flexible and robust software package for processing streaming data. Changes:python 3 support; new API; bug fixes and enhancements
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About: A Matlab implementation of Uncorrelated Multilinear Discriminant Analysis (UMLDA) for dimensionality reduction of tensor data via tensor-to-vector projection Changes:Initial Announcement on mloss.org.
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About: SVMlin: Fast Linear SVMs for Supervised and Semi-supervised Learning Changes:Initial Announcement on mloss.org.
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About: Fast Runtime-Flexible Multi-dimensional Arrays and Views for C++ Changes:Initial Announcement on mloss.org.
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About: CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python [...] Changes:Initial Announcement on mloss.org.
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About: You can use the software in this package to efficiently sample from Changes:Initial Announcement on mloss.org.
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About: Logic Forest Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.077571
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About: The original Random Forests implementation by Breiman and Cutler. Changes:Initial Announcement on mloss.org.
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About: PLEASD: A Matlab Toolbox for Structured Learning Changes:Initial Announcement on mloss.org.
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About: A recommender systems research framework aimed at modeling non-stationary environments. Changes:Initial Announcement on mloss.org.
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About: The incomplete Cholesky decomposition for a dense symmetric positive definite matrix A is a simple way of approximating A by a matrix of low rank (you can choose the rank). It has been used [...] Changes:Initial Announcement on mloss.org.
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About: A Java library to create, process and manage mixtures of exponential families. Changes:Initial Announcement on mloss.org.
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About: Matlab implementation of variational gaussian approximate inference for Bayesian Generalized Linear Models. Changes:Code restructure and bug fix.
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About: NetKit is an open-source Network Learning toolkit for statistical relational learning. Its architecture is extremely modular, making it easy to combine different learning algorithms. Changes:Initial Announcement on mloss.org.
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About: Fast Multidimensional GP Inference using Projected Additive Approximation Changes:Initial Announcement on mloss.org.
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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 L21-norm minimization can be justified from the viewpoint of half-quadratic (HQ) optimization, which facilitates convergence study and algorithmic development. In particular, a general formulation is accordingly proposed to unify L1-norm and L21-norm 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 non-convex correntropy objective. In terms of face recognition, we apply the proposed method to obtain an appearance-based model, called Sparse-Fisherfaces. Extensive experiments show that our method can select robust and sparse features, and outperforms several state-of-the-art subspace methods on largescale and open face recognition datasets. Changes:Initial Announcement on mloss.org. |