20 projects found that use the apache 2.0 license.
Showing Items 1-20 of 37 on page 1 of 2: 1 2 Next

Logo Aboleth 0.6.2

by dsteinberg - October 13, 2017, 01:21:35 CET [ Project Homepage BibTeX Download ] 940 views, 246 downloads, 3 subscriptions

About: A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Changes:

Hotfix release

  • fix random seeds
  • fix dropout sampling layers

Logo Aika 0.8

by molzberger - September 19, 2017, 18:10:43 CET [ Project Homepage BibTeX Download ] 1388 views, 436 downloads, 3 subscriptions

About: Aika is an open source text mining engine. It can automatically extract and annotate semantic information in text. In case this information is ambiguous, Aika will generate several hypothetical interpretations about the meaning of this text and retrieve the most likely one.

Changes:

Aika Version 0.8 (2017-09-17) - Optimization of the interpretation search using an upper bound on the interpretation weights. - Support for very large models with millions of neurons by suspending rarely used neurons to disk.

Aika Version 0.7 (2017-08-06) - Refactoring of the range model. Now the range begin and the range end can be treated independently of each other. Synapses now have three properties: range match, range output and range mapping. - The Iteration class has been merged into the document class. - Performance optimizations for the interpretation search in the SearchNode class. - Test case fixes - Class renaming: Option -> InterprNode, ExpandNode -> SearchNode - Lots of javadoc

Aika Version 0.6 (2017-07-01) - Mainly optimizations


Logo KeLP 2.2.1

by kelpadmin - August 7, 2017, 17:20:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18514 views, 3914 downloads, 3 subscriptions

About: Kernel-based Learning Platform (KeLP) is Java framework that supports the implementation of kernel-based learning algorithms, as well as an agile definition of kernel functions over generic data representation, e.g. vectorial data or discrete structures. The framework has been designed to decouple kernel functions and learning algorithms, through the definition of specific interfaces. Once a new kernel function has been implemented, it can be automatically adopted in all the available kernel-machine algorithms. KeLP includes different Online and Batch Learning algorithms for Classification, Regression and Clustering, as well as several Kernel functions, ranging from vector-based to structural kernels. It allows to build complex kernel machine based systems, leveraging on JSON/XML interfaces to instantiate prediction models without writing a single line of code.

Changes:

In addition to minor bug fixes, this release includes:

  • A new cache (FixSizeKernelCache) that can store a larger number of computations.

  • Evaluators for measuring the quality of Clustering algorithms.

Furthermore we also released the new module kelp-input-generator, that contains the facilities to parse text snippets and generate tree representations for KeLP!

Check out this new version from our repositories. API Javadoc is already available. Your suggestions will be very precious for us, so download and try KeLP 2.2.1!


Logo DynaML 1.4.1

by mandar2812 - April 20, 2017, 18:32:33 CET [ Project Homepage BibTeX Download ] 999 views, 236 downloads, 1 subscription

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.


Logo Armadillo library 7.800

by cu24gjf - March 8, 2017, 10:11:25 CET [ Project Homepage BibTeX Download ] 117856 views, 22903 downloads, 5 subscriptions

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About: Armadillo is a high quality C++ linear algebra library, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products).

Changes:
  • more accurate sparse eigen decomposition by eigs_sym() and eigs_gen()
  • more robust handling of non-square matrices by lu()
  • expanded qz() to optionally specify ordering of the Schur form
  • expanded .each_slice() in the Cube class to support matrix multiplication
  • expanded several functions to handle sparse matrices
  • added expmat_sym(), logmat_sympd(), sqrtmat_sympd() for handling symmetric matrices
  • added polyfit() and polyval() for polynomial fitting
  • fix for aliasing issue in convolution functions conv() and conv2()
  • fix for memory leak in the field class when compiling in C++11/C++14 mode

Logo revrand 1.0.0

by dsteinberg - January 29, 2017, 04:33:54 CET [ Project Homepage BibTeX Download ] 14904 views, 3130 downloads, 3 subscriptions

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

Changes:
  • 1.0 release!
  • Now there is a random search phase before optimization of all hyperparameters in the regression algorithms. This improves the performance of revrand since local optima are more easily avoided with this improved initialisation
  • Regression regularizers (weight variances) associated with each basis object, this approximates GP kernel addition more closely
  • Random state can be set for all random objects
  • Numerous small improvements to make revrand production ready
  • Final report
  • Documentation improvements

Logo AMIDST Toolbox 0.6.0

by ana - October 14, 2016, 19:35:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8170 views, 1493 downloads, 4 subscriptions

About: A Java Toolbox for Scalable Probabilistic Machine Learning.

Changes:
  • Added sparklink module implementing the integration with Apache Spark. More information here.
  • Fluent pattern in latent-variable-models
  • Predefined model implementing the concept drift detection

Detailed information can be found in the toolbox's web page


Logo Toupee 0.1

by nitbix - March 7, 2016, 20:29:59 CET [ Project Homepage BibTeX Download ] 1931 views, 469 downloads, 3 subscriptions

About: A Python based library for running experiments with Deep Learning and Ensembles on GPUs.

Changes:

Initial Announcement on mloss.org.


Logo PROFET 1.0.0

by Hamda - November 26, 2015, 13:20:28 CET [ Project Homepage BibTeX Download ] 2140 views, 626 downloads, 2 subscriptions

About: Software for Automatic Construction and Inference of DBNs Based on Mathematical Models

Changes:

Initial Announcement on mloss.org.


About: Efficient and Flexible Distributed/Mobile Deep Learning Framework, for python, R, Julia and more

Changes:

This version comes with Distributed and Mobile Examples


Logo Apache Mahout 0.11.1

by gsingers - November 9, 2015, 16:12:06 CET [ Project Homepage BibTeX Download ] 26698 views, 6617 downloads, 3 subscriptions

About: Apache Mahout is an Apache Software Foundation project with the goal of creating both a community of users and a scalable, Java-based framework consisting of many machine learning algorithm [...]

Changes:

Apache Mahout introduces a new math environment we call Samsara, for its theme of universal renewal. It reflects a fundamental rethinking of how scalable machine learning algorithms are built and customized. Mahout-Samsara is here to help people create their own math while providing some off-the-shelf algorithm implementations. At its core are general linear algebra and statistical operations along with the data structures to support them. You can use is as a library or customize it in Scala with Mahout-specific extensions that look something like R. Mahout-Samsara comes with an interactive shell that runs distributed operations on a Spark cluster. This make prototyping or task submission much easier and allows users to customize algorithms with a whole new degree of freedom. Mahout Algorithms include many new implementations built for speed on Mahout-Samsara. They run on Spark 1.3+ and some on H2O, which means as much as a 10x speed increase. You’ll find robust matrix decomposition algorithms as well as a Naive Bayes classifier and collaborative filtering. The new spark-itemsimilarity enables the next generation of cooccurrence recommenders that can use entire user click streams and context in making recommendations.


Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 18905 views, 3314 downloads, 3 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. The newest version of xgboost now supports distributed learning on various platforms such as hadoop, mpi and scales to even larger problems

Changes:
  • Distributed version of xgboost that runs on YARN, scales to billions of examples

  • Direct save/load data and model from/to S3 and HDFS

  • Feature importance visualization in R module, by Michael Benesty

  • Predict leaf index

  • Poisson regression for counts data

  • Early stopping option in training

  • Native save load support in R and python

  • xgboost models now can be saved using save/load in R

  • xgboost python model is now pickable

  • sklearn wrapper is supported in python module

  • Experimental External memory version


Logo streamDM 0.0.1

by abifet - April 28, 2015, 12:34:00 CET [ Project Homepage BibTeX Download ] 2713 views, 912 downloads, 1 subscription

About: streamDM is a new open source data mining and machine learning library, designed on top of Spark Streaming, an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of data streams.

Changes:

Initial Announcement on mloss.org.


Logo Hivemall 0.3

by myui - March 13, 2015, 17:08:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13428 views, 2320 downloads, 3 subscriptions

About: Hivemall is a scalable machine learning library running on Hive/Hadoop.

Changes:
  • Supported Matrix Factorization
  • Added a support for TF-IDF computation
  • Supported AdaGrad/AdaDelta
  • Supported AdaGradRDA classification
  • Added normalization scheme

Logo Rabit 0.1.0

by crowwork - January 21, 2015, 18:48:46 CET [ Project Homepage BibTeX Download ] 2474 views, 810 downloads, 1 subscription

About: rabit (Reliable Allreduce and Broadcast Interface) is a light weight library that provides a fault tolerant interface of Allreduce and Broadcast for portable , scalable and reliable distributed machine learning programs. Rabit programs can run on various platforms such as Hadoop, MPI and no installation is needed. Rabit now support kmeans clustering, and distributed xgboost: an extremely efficient disrtibuted boosted tree(GBDT) toolkit.

Changes:

Initial Announcement on mloss.org.


Logo ExtRESCAL 0.7.2

by nzhiltsov - January 20, 2015, 00:35:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10188 views, 1894 downloads, 2 subscriptions

About: Scalable tensor factorization

Changes:
  • Improve (speed up) initialization of A by summation

Logo Semi Stochastic Gradient Descent 1.0

by konkey - July 9, 2014, 04:28:47 CET [ BibTeX BibTeX for corresponding Paper Download ] 4679 views, 1084 downloads, 1 subscription

About: Efficient implementation of Semi-Stochastic Gradient Descent algorithm (S2GD) for training logistic regression (L2-regularized).

Changes:

Initial Announcement on mloss.org.


Logo Encog Machine Learning Framework 3.2

by jeffheaton - July 5, 2014, 23:47:06 CET [ Project Homepage BibTeX Download ] 8160 views, 2574 downloads, 1 subscription

About: Encog is a Machine Learning framework for Java, C#, Javascript and C/C++ that supports SVM's, Genetic Programming, Bayesian Networks, Hidden Markov Models and other algorithms.

Changes:

Changes for Encog 3.2:

Issue #53: Fix Out Of Range Bug In BasicMLSequenceSet. Issue #52: Unhandled exception in Encog.Util.File.ResourceLoader.CreateStream (ResourceLoader.cs) Issue #50: Concurrency bugs in PruneIncremental Issue #48: Unit Tests Failing - TestHessian Issue #46: Couple of small fixes - Temporal DataSet and SCG training Issue #45: Fixed EndMinutesStrategy to correctly evaluate ShouldStop after the specified number of minutes have elapsed. Issue #44: Encog.ML.Data.Basic.BasicMLDataPairCentroid.Add() & .Remove() Issue #43: Unit Tests Failing - Matrix not full rank Issue #42: Nuget - NuSpec Issue #36: Load Examples easier


About: RLLib is a lightweight C++ template library that implements incremental, standard, and gradient temporal-difference learning algorithms in Reinforcement Learning. It is an optimized library for robotic applications and embedded devices that operates under fast duty cycles (e.g., < 30 ms). RLLib has been tested and evaluated on RoboCup 3D soccer simulation agents, physical NAO V4 humanoid robots, and Tiva C series launchpad microcontrollers to predict, control, learn behaviors, and represent learnable knowledge. The implementation of the RLLib library is inspired by the RLPark API, which is a library of temporal-difference learning algorithms written in Java.

Changes:

Current release version is v2.0.


Logo MShadow 1.0

by antinucleon - April 10, 2014, 02:57:54 CET [ Project Homepage BibTeX Download ] 3666 views, 934 downloads, 1 subscription

About: Lightweight CPU/GPU Matrix/Tensor Template Library in C++/CUDA. Support element-wise expression expand in high performance. Code once, run smoothly on both GPU and CPU

Changes:

Initial Announcement on mloss.org.


Showing Items 1-20 of 37 on page 1 of 2: 1 2 Next