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About: Use the power of crowdsourcing to create ensembles. Changes:Initial Announcement on mloss.org.
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About: Classification rule based on Bayesian naive Bayes models with feature selection bias corrected Changes:Fetched by r-cran-robot on 2012-12-01 00:00:07.510624
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About: Classification and Regression Training in Parallel Using NetworkSpaces: Augment some caret functions using parallel processing Changes:Initial Announcement on mloss.org.
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About: FAST is an implementation of Hidden Markov Models with Features. It allows features to modify both emissions and transition probabilities. Changes:Initial Announcement on mloss.org.
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About: LOFS is a software toolbox for online streaming feature selection Changes:Initial Announcement on mloss.org.
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About: CN24 is a complete semantic segmentation framework using fully convolutional networks. Changes:Initial Announcement on mloss.org.
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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: Crino: a neural-network library based on Theano Changes:1.0.0 (7 july 2014) : - Initial release of crino - Implements a torch-like library to build artificial neural networks (ANN) - Provides standard implementations for : * auto-encoders * multi-layer perceptrons (MLP) * deep neural networks (DNN) * input output deep architecture (IODA) - Provides a batch-gradient backpropagation algorithm, with adaptative learning rate
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About: Approximate Rank One FACtorization of tensors. An algorithm for factorization of three-way-tensors and determination of their rank, includes example applications. Changes:Initial Announcement on mloss.org.
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About: A Matlab implementation of Uncorrelated Multilinear PCA (UMPCA) for dimensionality reduction of tensor data via tensor-to-vector projection Changes:Initial Announcement on mloss.org.
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About: DynaML is a Scala environment for conducting research and education in Machine Learning. DynaML comes packaged with a powerful library of classes implementing predictive models and a Scala REPL where one can not only build custom models but also play around with data work-flows. Changes:Initial Announcement on mloss.org.
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About: Denoising images via normalized convolution Changes:Initial Announcement on mloss.org.
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About: This software is designed for learning translation invariant kernels for classification with support vector machines. Changes:Initial Announcement on mloss.org.
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About: Embarrassingly Parallel Array Computing: EPAC is a machine learning workflow builder. Changes:Initial Announcement on mloss.org.
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About: revised version of BACOM Changes:Initial Announcement on mloss.org.
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About: minFunc is a Matlab function for unconstrained optimization of differentiable real-valued multivariate functions using line-search 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.
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About: Jatecs is an open source Java library focused on automatic text categorization. Changes:Initial Announcement on mloss.org.
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About: This is a Matlab/C++ "toolbox" of code for learning and inference with graphical models. It is focused on parameter learning using marginalization in the high-treewidth setting. Changes:Initial Announcement on mloss.org.
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About: A MATLAB toolkit for performing generalized regression with equality/inequality constraints on the function value/gradient. Changes:Initial Announcement on mloss.org.
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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.
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