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About: This software implements the DeltaLDA model, which is a modification of the Latent Dirichlet Allocation (LDA) model. DeltaLDA can use multiple topic mixing weight priors to jointly model multiple [...] Changes:-fixed some npy_intp[] memory leaks -fixed phi normalization bug
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About: Denoising images via normalized convolution Changes:Initial Announcement on mloss.org.
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About: Investigation of dependencies between multiple data sources allows the discovery of regularities and interactions that are not seen in individual data sets. The demand for such methods is increasing with the availability and size of co-occurring observations in computational biology, open data initiatives, and in other domains. We provide practical, open access implementations of general-purpose algorithms that help to realize the full potential of these information sources. Changes:Three independent modules (drCCA, pint, MultiWayCCA) have been added.
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About: A method to optimize the hyperparameters for machine learning methods implemented in Scikit-learn based on Derivative Free Optimization Changes:Initial Announcement on mloss.org.
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About: DIANNE is a modular software framework for designing, training and evaluating artificial neural networks on heterogeneous, distributed infrastructure . It is built on top of OSGi and AIOLOS and can transparently deploy and redeploy (parts of) a neural network on multiple machines, as well as scale up training on a compute cluster. Changes:Initial Announcement on mloss.org.
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About: DDN learns and visualize differential dependency networks from condition-specific data. Changes:Initial Announcement on mloss.org.
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About: Easy differential privacy Changes:Initial Announcement on mloss.org.
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About: DiffSharp is a functional automatic differentiation (AD) library providing gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products as higher-order functions. It allows exact and efficient calculation of derivatives, with support for nesting. Changes:Fixed: Bug fix in forward AD implementation of Sigmoid and ReLU for D, DV, and DM (fixes #16, thank you @mrakgr) Improvement: Performance improvement by removing several more Parallel.For and Array.Parallel.map operations, working better with OpenBLAS multithreading Added: Operations involving incompatible dimensions of DV and DM will now throw exceptions for warning the user
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About: This software implements the Dirichlet Forest (DF) Prior within the Latent Dirichlet Allocation (LDA) model. When combined with LDA, the Dirichlet Forest Prior allows the user to encode domain knowledge (must-links and cannot-links between words) into the prior on topic-word multinomials. Changes:Initial Announcement on mloss.org.
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About: Disco is an open-source implementation of the [Map-Reduce framework](http://en.wikipedia.org/wiki/MapReduce) for distributed computing. As the original framework, Disco supports parallel [...] Changes:Initial Announcement on mloss.org.
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About: Distributed optimization: Support Vector Machines and LASSO regression on distributed data Changes:Initial Upload
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About: Divvy is a Mac OS X application for performing dimensionality reduction, clustering, and visualization. Changes:Initial Announcement on mloss.org.
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About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. Changes:This release adds a bunch of new image processing routines as well as many minor usability improvements and bug fixes.
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About: The DL-Learner framework contains several algorithms for supervised concept learning in Description Logics (DLs) and OWL. Changes:See http://dl-learner.org/development/changelog/.
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About: DRVQ is a C++ library implementation of dimensionality-recursive vector quantization, a fast vector quantization method in high-dimensional Euclidean spaces under arbitrary data distributions. It is an approximation of k-means that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a by-product of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast. 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: dysii is a C++ library for distributed probabilistic inference and learning in large-scale dynamical systems. It provides methods such as the Kalman, unscented Kalman, and particle filters and [...] Changes:Initial Announcement on mloss.org.
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About: EANT Without Structural Optimization is used to learn a policy in either complete or partially observable reinforcement learning domains of continuous state and action space. Changes:Initial Announcement on mloss.org.
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About: The Easysvm package provides a set of tools based on the Shogun toolbox allowing to train and test SVMs in a simple way. Changes:Fixes for shogun 0.7.3.
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About: Eblearn is an object-oriented C++ library that implements various Changes:Initial Announcement on mloss.org.
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