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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 WEKA 3.7.11

by mhall - April 24, 2014, 10:13:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37684 views, 5391 downloads, 2 subscriptions

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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...]

Changes:

In core weka:

  • Bagging and RandomForest are now faster if the base learner is a WeightedInstancesHandler
  • Speed-ups for REPTree and other classes that use entropy calculations
  • Many other code improvements and speed-ups
  • Additional statistics available in the output of LinearRegression and SimpleLinearRegression. Contributed by Chris Meyer
  • Reduced memory consumption in BayesNet
  • Improvements to the package manager: load status of individual packages can now be toggled to prevent a package from loading; "Available" button now displays the latest version of all available packages that are compatible with the base version of Weka
  • RandomizableFilteredClassifier
  • Canopy clusterer
  • ImageViewer KnowledgeFlow component
  • PMML export support for Logistic. Infrastructure and changes contributed by David Person
  • Extensive tool-tips now displayed in the Explorer's scheme selector tree lists
  • Join KnowledgeFlow component for performing an inner join on two incoming streams/data sets

In packages:

  • IWSSembeded package, contributed by Pablo Bermejo
  • CVAttributeEval package, contributed by Justin Liang
  • distributedWeka package for Hadoop
  • Improvements to multiLayerPerceptrons and addtion of MLPAutoencoder
  • Code clean-up in many packages

Logo libstb 1.8

by wbuntine - April 24, 2014, 09:02:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4158 views, 793 downloads, 1 subscription

About: Generalised Stirling Numbers for Pitman-Yor Processes: this library provides ways of computing generalised 2nd-order Stirling numbers for Pitman-Yor and Dirichlet processes. Included is a tester and parameter optimiser. This accompanies Buntine and Hutter's article: http://arxiv.org/abs/1007.0296, and a series of papers by Buntine and students at NICTA and ANU.

Changes:

Moved repository to GitHub, and added thread support to use the main table lookups in multi-threaded code.


Logo libAGF 0.9.7

by Petey - April 15, 2014, 04:55:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7455 views, 1510 downloads, 1 subscription

About: C++ software for statistical classification, probability estimation and interpolation/non-linear regression using variable bandwidth kernel estimation.

Changes:

New in Version 0.9.7:

  • multi-class classification generalizes class-borders algorithm using a recursive control language
  • hierarchical clustering
  • improved pre-processing

Logo GradMC 2.00

by tur - April 14, 2014, 15:48:48 CET [ BibTeX Download ] 1379 views, 485 downloads, 1 subscription

About: GradMC is an algorithm for MR motion artifact removal implemented in Matlab

Changes:

Added support for multi-rigid motion correction.


Logo Somoclu 1.3.1

by peterwittek - April 10, 2014, 06:41:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2998 views, 568 downloads, 2 subscriptions

About: Somoclu is a massively parallel implementation of self-organizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes.

Changes:
  • Initial Windows support through GCC on Windows.
  • Better I/O separation for the Python, R, and MATLAB interfaces.
  • Bug fixes: major MPI initialization bug fixed.

Logo MShadow 1.0

by antinucleon - April 10, 2014, 02:57:54 CET [ Project Homepage BibTeX Download ] 547 views, 124 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.


Logo CXXNET 0.1

by antinucleon - April 10, 2014, 02:47:08 CET [ Project Homepage BibTeX Download ] 598 views, 126 downloads, 1 subscription

About: CXXNET (spelled as: C plus plus net) is a neural network toolkit build on mshadow(https://github.com/tqchen/mshadow). It is yet another implementation of (convolutional) neural network. It is in C++, with about 1000 lines of network layer implementations, easily configuration via config file, and can get the state of art performance.

Changes:

Initial Announcement on mloss.org.


Logo JMLR MOA Massive Online Analysis Nov-13

by abifet - April 4, 2014, 03:50:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10537 views, 4172 downloads, 1 subscription

About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license.

Changes:

New version November 2013


Logo SAMOA 0.0.1

by gdfm - April 2, 2014, 17:09:08 CET [ Project Homepage BibTeX Download ] 471 views, 124 downloads, 1 subscription

About: SAMOA is a platform for mining big data streams. It is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms.

Changes:

Initial Announcement on mloss.org.


Showing Items 51-60 of 535 on page 6 of 54: Previous 1 2 3 4 5 6 7 8 9 10 11 Next Last