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Logo JMLR dlib ml 19.0

by davis685 - June 25, 2016, 23:04:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 141441 views, 23090 downloads, 4 subscriptions

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.


This release adds a deep learning toolkit to dlib that has a clean and fully documented C++11 API. It also includes CPU and GPU support, binds to cuDNN, can train on multiple GPUs at a time, and comes with a pretrained imagenet model based on ResNet34.

The release also adds a number of other improvements such as new elastic net regularized solvers and QP solvers, improved MATLAB binding tools, and other usability tweaks and optimizations.

Logo revrand 0.4.1

by dsteinberg - June 24, 2016, 05:58:05 CET [ Project Homepage BibTeX Download ] 2748 views, 535 downloads, 3 subscriptions

About: A library of scalable Bayesian generalised linear models with fancy features

  • Allow for non-learnable likelihood arguments (per datum) in the glm
  • Hotfix for glm prediction sampling functions

Logo JMLR MLPACK 2.0.2

by rcurtin - June 20, 2016, 22:23:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 59499 views, 10924 downloads, 6 subscriptions

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About: A scalable, fast C++ machine learning library, with emphasis on usability.

  • Added the function LSHSearch::Projections(), which returns an arma::cube with each projection table in a slice (#663). Instead of Projection(i), you should now use Projections().slice(i).
  • A new constructor has been added to LSHSearch that creates objects using projection tables provided in an arma::cube (#663).
  • LSHSearch projection tables refactored for speed (#675).
  • Handle zero-variance dimensions in DET (#515).
  • Add MiniBatchSGD optimizer (src/mlpack/core/optimizers/minibatch_sgd/) and allow its use in mlpack_logistic_regression and mlpack_nca programs.
  • Add better backtrace support from Grzegorz Krajewski for Log::Fatal messages when compiled with debugging and profiling symbols. This requires libbfd and libdl to be present during compilation.
  • CosineTree test fix from Mikhail Lozhnikov (#358).
  • Fixed HMM initial state estimation (#600).
  • Changed versioning macros _MLPACKVERSION_MAJOR, _MLPACKVERSION_MINOR, and _MLPACKVERSION_PATCH to MLPACK_VERSION_MAJOR, MLPACK_VERSION_MINOR, and MLPACK_VERSION_PATCH. The old names will remain in place until mlpack 3.0.0.
  • Renamed mlpack_allknn, mlpack_allkfn, and mlpack_allkrann to mlpack_knn, mlpack_kfn, and mlpack_krann. The mlpack_allknn, mlpack_allkfn, and mlpack_allkrann programs will remain as copies until mlpack 3.0.0.
  • Add --random_initialization option to mlpack_hmm_train, for use when no labels are provided.
  • Add --kill_empty_clusters option to mlpack_kmeans and KillEmptyClusters policy for the KMeans class (#595, #596).

Logo SparklingGraph 0.0.6

by riomus - June 17, 2016, 14:49:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1947 views, 344 downloads, 2 subscriptions

About: Large scale, distributed graph processing made easy.


Bug fixes, Graph generators

Logo Salad 0.6.1

by chwress - June 17, 2016, 11:26:34 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10784 views, 2023 downloads, 3 subscriptions

About: A Content Anomaly Detector based on n-Grams


A teeny tiny fix to correctly handle input strings shorter than a registers width

Logo scikit multilearn 0.0.3

by niedakh - June 15, 2016, 19:28:32 CET [ Project Homepage BibTeX Download ] 369 views, 72 downloads, 2 subscriptions

About: A native Python, scikit-compatible, implementation of a variety of multi-label classification algorithms.


Initial Announcement on

Logo ADENINE 0.1.3

by samuelefiorini - June 13, 2016, 11:10:36 CET [ Project Homepage BibTeX Download ] 362 views, 50 downloads, 2 subscriptions

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, dimensionality reduction and clustering tasks.


Initial Announcement on

Logo JMLR Information Theoretical Estimators 0.63

by szzoli - June 9, 2016, 23:42:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 101643 views, 19572 downloads, 3 subscriptions

About: ITE (Information Theoretical Estimators) is capable of estimating many different variants of entropy, mutual information, divergence, association measures, cross quantities and kernels on distributions. Thanks to its highly modular design, ITE supports additionally (i) the combinations of the estimation techniques, (ii) the easy construction and embedding of novel information theoretical estimators, and (iii) their immediate application in information theoretical optimization problems.

  • Conditional Shannon entropy estimation: added.

  • Conditional Shannon mutual information estimation: included.

Logo JMLR GPstuff 4.7

by avehtari - June 9, 2016, 17:45:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 33034 views, 7948 downloads, 3 subscriptions

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About: The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods.


2016-06-09 Version 4.7

Development and release branches available at

New features

  • Simple Bayesian Optimization demo


  • Improved use of PSIS
  • More options added to gp_monotonic
  • Monotonicity now works for additive covariance functions with selected variables
  • Possibility to use gpcf_squared.m-covariance function with derivative observations/monotonicity
  • Default behaviour made more robust by changing default jitter from 1e-9 to 1e-6
  • LA-LOO uses the cavity method as the default (see Vehtari et al (2016). Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models. JMLR, accpeted for publication)
  • Selected variables -option works now better with monotonicity


  • small error in derivative observation computation fixed
  • several minor bug fixes

Logo Multiagent Decision Process Toolbox 0.4

by faoliehoek - June 2, 2016, 17:38:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2528 views, 575 downloads, 3 subscriptions

About: The Multiagent decision process (MADP) Toolbox is a free C++ software toolbox for scientific research in decision-theoretic planning and learning in multiagent systems.


-Includes freshly written spirit parser for .pomdp files. -Includes new code for pruning POMDP vectors; obviates dependence on Cassandra's code and old LP solve version. -Includes new factor graph solution code -Generalized firefighting CGBG domain added -Simulation class for Factored Dec-POMDPs and TOI Dec-MDPs -Approximate BG clustering methods and kGMAA with clustering.

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