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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.
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About: An audio editing tool for single-channel source separation. Changes:Stereo processing, bug fixes, UI updates.
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About: Torch5 provides a matlab-like environment for state-of-the-art machine learning algorithms. It is easy to use and provides a very efficient implementation, thanks to a easy and fast scripting [...] Changes:Initial Announcement on mloss.org.
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About: The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL and utilizes Intel Integrated Performance [...] Changes:Initial Announcement on mloss.org. |
About: Likelihood-based Boosting for Generalized mixed models Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.366545
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About: A library for artificial neural networks. Changes:Added algorithms:
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About: AISAIC software for analyzing human DNA copy numbers and detecting significant copy number alterations Changes:Initial Announcement on mloss.org.
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About: A Graphical Tool for Designing and Training Deep Neural Networks Changes:
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About: Python module for machine learning multivariate time series Changes:Initial Announcement on mloss.org.
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About: Correlative Matrix Mapping (CMM) provides a supervised linear data mapping into a Euclidean subspace of given dimension. Applications include denoising, visualization, label-specific data preprocessing, and assessment of data attribute pairs relevant for the supervised mapping. Solving auto-association problems yields linear multidimensional scaling, similar to PCA, but usually with more faithful low-dimensional mappings. Changes:Tue Jul 5 14:40:03 CEST 2011 - Bugfixes and cleanups
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About: Local alignment kernels measure the similarity between two sequences by summing up scores obtained from local alignments with gaps of the sequences. Changes:Initial Announcement on mloss.org.
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About: The JINSECT toolkit is a Java-based toolkit and library that supports and demonstrates the use of n-gram graphs within Natural Language Processing applications, ranging from summarization and summary evaluation to text classi?cation and indexing. Changes:
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About: Data-efficient policy search framework using probabilistic Gaussian process models Changes:Initial Announcement on mloss.org.
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About: The mission of this project is to build and support a community interested in machine learning and machine intelligence based on modeling the neocortex and the principles upon which it works. Changes:Initial Announcement on mloss.org.
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About: MLwizard recommends and optimizes classification algorithms based on meta-learning and is a software wizard fully integrated into RapidMiner but can be used as library as well. Changes:Faster parameter optimization using genetic algorithm with predefined start population.
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About: A Matlab script for learning vector-valued functions and kernels on the output space. Changes:Added code for learning low-rank output kernels.
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About: We provide some preliminary code for multiclass multiple kernel learning in Matlab using CPLEX as a base solver. Changes:Initial Announcement on mloss.org.
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About: CRFSuite is a speed-oriented implementation of Conditional Random Fields (CRFs). This software features: parameter estimation using SGD and L-BFGS, l1/l2 regularization, simple data I/O format, etc. Changes:Initial Announcement on mloss.org.
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About: This is a Perl module that implements a variety of semantic similarity and relatedness measures based on information found in the lexical database WordNet. In particular, it supports the measures of [...] Changes:Initial Announcement on mloss.org.
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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
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