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Showing Items 1-20 of 674 on page 1 of 34: 1 2 3 4 5 6 Next Last

Logo A Parallel LDA Learning Toolbox 1.0

by yanjianfeng - January 24, 2014, 11:48:07 CET [ BibTeX Download ] 5153 views, 1942 downloads, 0 subscriptions

About: We introduces PLL, a parallel LDA learning toolbox for big topic modeling.

Changes:

Fix some compiling errors.


Logo BayesOpt, a Bayesian Optimization toolbox 0.8.2

by rmcantin - December 9, 2015, 04:53:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 45896 views, 8241 downloads, 0 subscriptions

About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinear-optimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python.

Changes:

-Fixed bug in save/restore. -Fixed bug in initial design.


Logo 1SpectralClustering 1.2

by tbuehler - May 1, 2018, 19:26:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18449 views, 3644 downloads, 0 subscriptions

About: A fast and scalable graph-based clustering algorithm based on the eigenvectors of the nonlinear 1-Laplacian.

Changes:
  • improved optimization of ncut and rcut criterion
  • optimized eigenvector initialization
  • changed default values for number of runs
  • several internal optimizations
  • made console output more informative

Logo A framework for benchmarking of feature selection algorithms and cost functions v1.3

by msreis - August 4, 2017, 00:19:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3833 views, 702 downloads, 0 subscriptions

About: An open-source framework for benchmarking of feature selection algorithms and cost functions.

Changes:

Initial Announcement on mloss.org.


Logo A Library for Online Streaming Feature Selection 1.0

by ykui713 - November 25, 2015, 13:23:01 CET [ BibTeX Download ] 2962 views, 1227 downloads, 0 subscriptions

About: LOFS is a software toolbox for online streaming feature selection

Changes:

Initial Announcement on mloss.org.


Logo A Local and Parallel Computation Toolbox for Gaussian Process Regression 1.0

by cwpark - March 19, 2012, 17:21:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15502 views, 5059 downloads, 0 subscriptions

About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software.

Changes:

Initial Announcement on mloss.org.


Logo A Pattern Recognizer In Lua with ANNs v0.4.1

by pakozm - December 3, 2015, 15:01:36 CET [ Project Homepage BibTeX Download ] 14953 views, 3432 downloads, 0 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:
  • Updated home repository link to follow april-org github organization.
  • Improved serialize/deserialize functions, reimplemented all the serialization procedure.
  • Added exceptions support to LuaPkg and APRIL-ANN, allowing to capture C++ errors into Lua code.
  • Added set class.
  • Added series class.
  • Added data_frame class, similar to Python Pandas DataFrame.
  • Serialization and deserilization have been updated with more robust and reusable API, implemented in util.serialize() and util.deserialize() functions.
  • Added matrix.ext.broadcast utility (similar to broadcast in numpy).
  • Added ProbablisitcMatrixANNComponent, which allow to implement probabilistic mixtures of posteriors and/or likelihoods.
  • Added batch normalization ANN component.
  • Allowing matrix.join to add new axis.
  • Added methods prod(), cumsum() and cumprod() at matrix classes.
  • Added methods count_eq() and count_neq() at matrix classes.
  • Serializable objects API have been augmented with methods ctor_name() and
    ctor_params() in Lua, refered to luaCtorName() and luaCtorParams() in C++.
  • Added cast.to to dynamic cast C++ objects pushed into Lua, allowing to convert base class objects into any of its derived classes.
  • Added matrix.sparse as valid values for targets in ann.loss.mse and
    ann.loss.cross_entropy.
  • Changed matrix metamethods __index and __newindex, allowing to use
    matrix objects with standard Lua operator[].
  • Added matrix.masked_fill and matrix.masked_copy matrix.
  • Added matrix.indexed_fill and matrix.indexed_copy matrix.
  • Added ann.components.probabilistic_matrix, and its corresponding specializations ann.components.left_probabilistic_matrix and
    ann.components.right_probabilistic_matrix.
  • Added operator[] in the right side of matrix operations.
  • Added ann.components.transpose.
  • Added max_gradients_norm in traianble.supervised_trainer, to avoid gradients exploding.
  • Added ann.components.actf.sparse_logistic a logistic activation function with sparsity penalty.
  • Simplified math.add, math.sub, ... and other math extensions for reductions, their original behavior can be emulated by using bind function.
  • Added bind function to freeze any positional argument of any Lua function.
  • Function stats.boot uses multiple_unpack to allow a table of sizes and the generation of multiple index matrices.
  • Added multiple_unpack Lua function.
  • Added __tostring metamethod to numeric memory blocks in Lua.
  • Added dataset.token.sparse_matrix, a dataset which allow to traverse by rows a sparse matrix instance.
  • Added matrix.sparse.builders.dok, a builder which uses the Dictionary-of-Keys format to construct a sparse matrix from scratch.
  • Added method data to numeric matrix classes.
  • Added methods values, indices, first_index to sparse matrix class.
  • Fixed bugs when reading bad formed CSV files.
  • Fixed bugs at statistical distributions.
  • FloatRGB bug solved on equal (+=, -=, ...) operators. This bug affected ImageRGB operations such as resize.
  • Solved problems when chaining methods in Lua, some objects end to be garbage collected.
  • Improved support of strings in auto-completion (rlcompleter package).
  • Solved bug at SparseMatrix<T> when reading it from a file.
  • Solved bug in Image<T>::rotate90_cw methods.
  • Solved bug in SparseMatrix::toDense() method.

C/C++

  • Better LuaTable accessors, using [] operator.
  • Implementation of matrix __index, __newindex and __call metamethods in C++.
  • Implementation of matProd(), matCumSum() and matCumProd() functions.
  • Implementation of matCountEq() and matCountNeq() functions for
    Matrix<T>.
  • Updated matrix_ext_operations.h to change API of matrix operations. All functions have been overloaded to accept an in-place operation and another version which receives a destination matrix.
  • Adding iterators to language models.
  • Added MatrixScalarMap2 which receives as input2 a SparaseMatrix instance. This functions needs to be generalized to work with CPU and CUDA.
  • The method SparseMatrix<T>::fromDenseMatrix() uses a DOKBuilder object to build the sparse matrix.
  • The conversion of a Matrix<T> into a SparseMatrix<T> has been changed from a constructor overload to the static method
    SparseMatrix<T>::fromDenseMatrix().
  • Added support for IPyLua.
  • Optimized matrix access for confusion matrix.
  • Minor changes in class.lua.
  • Improved binding to avoid multiple object copies when pushing C++ objects.
  • Added Git commit hash and compilation time.

Logo A Regularized Correntropy Framework for Robust Pattern Recognition 1.0

by openpr_nlpr - June 3, 2013, 09:59:51 CET [ Project Homepage BibTeX Download ] 6327 views, 1556 downloads, 0 subscriptions

About: This letter proposes a new multiple linear regression model using regularized correntropy for robust pattern recognition. First, we motivate the use of correntropy to improve the robustness of the classicalmean square error (MSE) criterion that is sensitive to outliers. Then an l1 regularization scheme is imposed on the correntropy to learn robust and sparse representations. Based on the half-quadratic optimization technique, we propose a novel algorithm to solve the nonlinear optimization problem. Second, we develop a new correntropy-based classifier based on the learned regularization scheme for robust object recognition. Extensive experiments over several applications confirm that the correntropy-based l1 regularization can improve recognition accuracy and receiver operator characteristic curves under noise corruption and occlusion.

Changes:

Initial Announcement on mloss.org.


Logo A Statistical Audit for Reproducibility and Altermate Analysis 0.1

by matloff - September 5, 2017, 06:51:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2628 views, 610 downloads, 0 subscriptions

About: Tool aimed at helping remedy the reproducibility problem, specifically in the statistical and data wrangling aspects.

Changes:

Initial Announcement on mloss.org.


Logo ABACOC Adaptive Ball Cover for Classification 2.0

by kikot - May 29, 2015, 11:57:28 CET [ BibTeX BibTeX for corresponding Paper Download ] 9403 views, 2353 downloads, 0 subscriptions

About: Incremental (Online) Nonparametric Classifier. You can classify both points (standard) or matrices (multivariate time series). Java and Matlab code already available.

Changes:

version 2: parameterless system, constant model size, prediction confidence (for active learning).

NEW!! C++ version at: https://github.com/ilaria-gori/ABACOC


Logo Aboleth 0.7

by dsteinberg - December 14, 2017, 02:39:19 CET [ Project Homepage BibTeX Download ] 5484 views, 1539 downloads, 0 subscriptions

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

Changes:

Release 0.7.0

  • Update to TensorFlow r1.4.

  • Tutorials in the documentation on:

  • Interfacing with Keras

  • Saving/loading models

  • How to build a variety of regressors with Aboleth

  • New prediction module with some convenience functions, including freezing the weight samples during prediction.

  • Bayesian convolutional layers with accompanying demo.

  • Allow the number of samples drawn from a model to be varied by using placeholders.

  • Generalise the feature embedding layers to work on matrix inputs (instead of just column vectors).

  • Numerous numerical and usability fixes.


Logo Accord.NET Framework 3.8.0

by cesarsouza - October 23, 2017, 20:50:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 51978 views, 9054 downloads, 0 subscriptions

About: The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details.

Changes:

For a complete list of changes, please see the full release notes at the release details page at:

https://github.com/accord-net/framework/releases/tag/v3.8.0


Logo Aciqra 1.2.1

by Caglow - June 25, 2009, 23:30:22 CET [ BibTeX Download ] 5438 views, 2489 downloads, 0 subscriptions

About: A desktop planetarium and sky map program which shows the sky from anywhere on Earth at any time.

Changes:

Removed erroneous topocentric code. Increased maximum zoom for detail on planets.


Logo Action Recognition by Dense Trajectories 1.0

by openpr_nlpr - June 6, 2012, 11:38:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7987 views, 1356 downloads, 0 subscriptions

About: The code is for computing state-of-the-art video descriptors for action recognition. The most up-to-date information can be found at: http://lear.inrialpes.fr/people/wang/dense_trajectories

Changes:

Initial Announcement on mloss.org.


Logo ADAMS 17.12.0

by fracpete - December 20, 2017, 09:38:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 44775 views, 8056 downloads, 0 subscriptions

About: The Advanced Data mining And Machine learning System (ADAMS) is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes.

Changes:

Some highlights:

  • Code base was moved to Github
  • Nearly 90 new actors, 25 new conversions
  • much improved deeplearning4j module
  • experimental support for Microsoft's CNTK deep learning framework
  • rsync module
  • MEKA webservice module
  • improved support for image annotations
  • improved LaTeX support
  • Websocket support

Logo Adaptive Resonance Theory for Unsupervised Learning 1.0

by ibaze - November 13, 2008, 16:40:28 CET [ Project Homepage BibTeX Download ] 10935 views, 2627 downloads, 0 subscriptions

About: This software package includes the ART algorithms for unsupervised learning only. It is a family of four programs based on different ART algorithms (ART 1, ART 2A, ART 2A-C and ART Distance). All of [...]

Changes:

Initial Announcement on mloss.org.


Logo AdditiveGP Toolkit for Fast GP Inference using Projected Additive Approximation 0.1

by ejg20 - September 14, 2013, 21:25:18 CET [ BibTeX Download ] 7131 views, 1637 downloads, 0 subscriptions

About: Fast Multidimensional GP Inference using Projected Additive Approximation

Changes:

Initial Announcement on mloss.org.


Logo ADENINE 0.1.4

by samuelefiorini - February 17, 2017, 14:50:49 CET [ Project Homepage BibTeX Download ] 4948 views, 1221 downloads, 0 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, unsupervised feature learning and clustering tasks.

Changes:
  • Adenine can now distribute the execution of its pipelines on multiple machines via MPI
  • kNN data imputing strategy is now implemented
  • added python 2.7 and 3.5 support
  • stability improved and bug fixed

Logo AffectiveTweets 1.0.1

by felipebravom - May 14, 2018, 08:20:50 CET [ Project Homepage BibTeX Download ] 4395 views, 1086 downloads, 0 subscriptions

About: A WEKA package for analyzing emotion and sentiment of tweets.

Changes:

Initial Announcement on mloss.org.


Logo Agglomerative MeanShift Clustering 1.0.0

by openpr_nlpr - December 2, 2011, 04:38:13 CET [ Project Homepage BibTeX Download ] 4217 views, 1115 downloads, 0 subscriptions

About: Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets. For the purpose of algorithm speedup, an agglomerative MS clustering method called Agglo-MS was developed, along with its mode-seeking ability and convergence property analysis. The method is built upon an iterative query set compression mechanism which is motivated by the quadratic bounding optimization nature of MS. The whole framework can be efficiently implemented in linear running time complexity.

Changes:

Initial Announcement on mloss.org.


Showing Items 1-20 of 674 on page 1 of 34: 1 2 3 4 5 6 Next Last