Projects running under linux.
Showing Items 21-40 of 224 on page 2 of 12: Previous 1 2 3 4 5 6 7 Next Last

Logo A Pattern Recognizer In Lua with ANNs v0.3.1

by pakozm - May 30, 2014, 10:49:10 CET [ Project Homepage BibTeX Download ] 2192 views, 502 downloads, 2 subscriptions

About: APRIL-ANN toolkit (A Pattern Recognizer In Lua with Artificial Neural Networks). This toolkit incorporates ANN algorithms (as dropout, stacked denoising auto-encoders, convolutional neural networks), with other pattern recognition methods as hidden makov models (HMMs) among others.

Changes:
  • Removed bugs.
  • Added Travis CI support.
  • KNN and clustering algorithms.
  • ZCA and PCA whitening.
  • Quickprop and ASGD optimization algorithms.
  • QLearning trainer.
  • Sparse float matrices are available in CSC an CSR formats.
  • Compilation with Homebrew and MacPorts available.
  • Compilation issues in Ubuntu 12.04 solved.

Logo Weight HMM 1.0

by SongTao - May 27, 2014, 15:29:20 CET [ BibTeX Download ] 353 views, 102 downloads, 1 subscription

About: Discovering short linear protein motif based on selective training of profile hidden Markov models

Changes:

Initial Announcement on mloss.org.


Logo Mr. 1.0

by SongTao - May 27, 2014, 15:20:40 CET [ BibTeX Download ] 269 views, 96 downloads, 1 subscription

About: Discovering short linear protein motif based on selective training of profile hidden Markov models

Changes:

Initial Announcement on mloss.org.


Logo XGBoost v0.2

by crowwork - May 17, 2014, 07:27:59 CET [ Project Homepage BibTeX Download ] 1749 views, 291 downloads, 1 subscription

About: eXtreme gradient boosting (tree) library. Features: - Sparse feature format allows easy handling of missing values, and improve computation efficiency. - Efficient parallel implementation that optimizes memory and computation. - Python interface

Changes:

New features: - Python interface - New objectives: weighted training, pairwise rank, multiclass softmax - Comes with example script on Kaggle Higgs competition, 20 times faster than skilearn's GBRT


Logo Java deep neural networks with GPU 0.2.0-alpha

by hok - May 10, 2014, 14:22:30 CET [ Project Homepage BibTeX Download ] 854 views, 189 downloads, 2 subscriptions

About: GPU-accelerated java deep neural networks

Changes:

Initial Announcement on mloss.org.


Logo PredictionIO 0.7.0

by simonc - April 29, 2014, 20:59:57 CET [ Project Homepage BibTeX Download ] 5213 views, 1008 downloads, 2 subscriptions

About: Open Source Machine Learning Server

Changes:
  • Single machine version for small-to-medium scale deployments
  • Integrated GraphChi (disk-based large-scale graph computation) and algorithms: ALS, CCD++, SGD, CLiMF
  • Improved runtime for training and offline evaluation
  • Bug fixes

See release notes - https://predictionio.atlassian.net/secure/ReleaseNote.jspa?projectId=10000&version=11801


Logo RFD 1.0

by openpr_nlpr - April 28, 2014, 10:34:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 750 views, 165 downloads, 1 subscription

About: This is an unoptimized implementation of the RFD binary descriptor, which is published in the following paper. B. Fan, et al. Receptive Fields Selection for Binary Feature Description. IEEE Transaction on Image Processing, 2014. doi: http://dx.doi.org/10.1109/TIP.2014.2317981

Changes:

Initial Announcement on mloss.org.


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 ] 38466 views, 5543 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 ] 4473 views, 871 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 GradMC 2.00

by tur - April 14, 2014, 15:48:48 CET [ BibTeX Download ] 1486 views, 516 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 ] 3304 views, 636 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 ] 624 views, 160 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 ] 700 views, 160 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 Tapkee 1.0

by blackburn - April 10, 2014, 02:45:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5435 views, 1508 downloads, 1 subscription

About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction.

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 ] 10859 views, 4309 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 JMLR MultiBoost 1.2.02

by busarobi - March 31, 2014, 16:13:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 22078 views, 3908 downloads, 1 subscription

About: MultiBoost is a multi-purpose boosting package implemented in C++. It is based on the multi-class/multi-task AdaBoost.MH algorithm [Schapire-Singer, 1999]. Basic base learners (stumps, trees, products, Haar filters for image processing) can be easily complemented by new data representations and the corresponding base learners, without interfering with the main boosting engine.

Changes:

Major changes :

  • The “early stopping” feature can now based on any metric output with the --outputinfo command line argument.

  • Early stopping now works with --slowresume command line argument.

Minor fixes:

  • More informative output when testing.

  • Various compilation glitch with recent clang (OsX/Linux).


Logo JMLR EnsembleSVM 2.0

by claesenm - March 31, 2014, 08:06:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4508 views, 1585 downloads, 2 subscriptions

About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks.

Changes:

The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:

  1. Support for multithreading in training and prediction with ensemble models. Since both of these are embarassingly parallel, this has induced a significant speedup (3-fold on quad-core).
  2. Extensive programming framework for aggregation of base model predictions which allows highly efficient prototyping of new aggregation approaches. Additionally we provide several predefined strategies, including (weighted) majority voting, logistic regression and nonlinear SVMs of your choice -- be sure to check out the esvm-edit tool! The provided framework also allows you to efficiently program your own, novel aggregation schemes.
  3. Full code transition to C++11, the latest C++ standard, which enabled various performance improvements. The new release requires moderately recent compilers, such as gcc 4.7.2+ or clang 3.2+.
  4. Generic implementations of convenient facilities have been added, such as thread pools, deserialization factories and more.

The API and ABI have undergone significant changes, many of which are due to the transition to C++11.


Logo Libra 1.0.1

by lowd - March 30, 2014, 09:42:00 CET [ Project Homepage BibTeX Download ] 9531 views, 2049 downloads, 1 subscription

About: The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, sum-product networks, arithmetic circuits, and mixtures of trees.

Changes:

Version 1.0.1 (3/30/2014):

  • Several new algorithms -- acmn, learning ACs using MNs; idspn, SPN structure learning; mtlearn, learning mixtures of trees
  • Several new support programs -- spquery, for exact inference in SPNs; spn2ac, for converting SPNs to ACs
  • Renamed aclearnstruct to acbn
  • Replaced aclearnstruct -noac with separate bnlearn program
  • ...and many more small changes and fixes, throughout!

Logo JMLR fastclime 1.2.3

by colin1898 - March 10, 2014, 08:54:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1265 views, 323 downloads, 1 subscription

About: The package "fastclime" provides a method of recover the precision matrix efficiently by applying parametric simplex method. The computation is based on a linear optimization solver. It also contains a generic LP solver and a parameterized LP solver using parametric simplex method.

Changes:

Initial Announcement on mloss.org.


Showing Items 21-40 of 224 on page 2 of 12: Previous 1 2 3 4 5 6 7 Next Last