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About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the well-known 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.
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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: STK++: A Statistical Toolkit Framework in C++ Changes:Inegrating openmp to the current release. Many enhancement in the clustering project. bug fix
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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: 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: Bayesian Prediction with High-order Interactions Changes:Fetched by r-cran-robot on 2012-12-01 00:00:03.777292
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About: In DMNS source, five databases are used in slover.cpp and data_veh_layer.cpp, these images and databases are included in this file, except munich database. Changes:Initial Announcement on mloss.org.
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About: Implementation of the multi-assignment clustering method for Boolean vectors. Changes:new bib added
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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: SMPyBandits: an Open-Source Research Framework for Single and Multi-Players Multi-Arms Bandits (MAB) Algorithms in Python Changes:Initial Announcement on mloss.org.
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About: Relaxed Lasso Changes:Fetched by r-cran-robot on 2013-04-01 00:00:07.978325
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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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About: Deep measuring net sequence(DMNS) is a sequence of three deep measuring nets, the later are deep fcn-based networks, directely output object category score, object orientation, location and scale simultaneously without any anchor boxes. DMNS acheived high accuracy in maneuvering target detection and geometrical measurements. Its average orientation error is less than 3.5 degree, loaction error less than 1.3 pixel, scale measuring error less than 10%, achieve a detection F1-score 96.5% in OAD, 91.8% in SVDS ,90.8% in Munich , 87.3% in OIRDS, outperforms SSD, Fater R-CNN, etc. Changes:Initial Announcement on mloss.org.
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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: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems 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: ADENINE (A Data ExploratioN pIpeliNE) is a machine learning framework for data exploration that encompasses state-of-the-art techniques for missing values imputing, data preprocessing, unsupervised feature learning and clustering tasks. Changes:
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