Projects supporting the matlab data format.
Showing Items 1-20 of 64 on page 1 of 4: 1 2 3 4 Next

Logo JMLR GPstuff 4.5

by avehtari - July 22, 2014, 14:03:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10339 views, 2849 downloads, 2 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.

Changes:

2014-07-22 Version 4.5

New features

  • Input dependent noise and signal variance.

    • Tolvanen, V., Jylänki, P. and Vehtari, A. (2014). Approximate Inference forNonstationary Heteroscedastic Gaussian Process Regression. In Proceedings of IEEE International Workshop on Machine Learning for Signal Processing, accepted for publication. Preprint http://arxiv.org/abs/1404.5443
  • Sparse stochastic variational inference model.

    • Hensman, J., Fusi, N. and Lawrence, N. D. (2013). Gaussian processes for big data. arXiv preprint http://arxiv.org/abs/1309.6835.
  • Option 'autoscale' in the gp_rnd.m to get split normal approximated samples from the posterior predictive distribution of the latent variable.

    • Geweke, J. (1989). Bayesian Inference in Econometric Models Using Monte Carlo Integration. Econometrica, 57(6):1317-1339.

    • Villani, M. and Larsson, R. (2006). The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis. Communications in Statistics - Theory and Methods, 35(6):1123-1140.

Improvements

  • New unit test environment using the Matlab built-in test framework (the old Xunit package is still also supported).
  • Precomputed demo results (including the figures) are now available in the folder tests/realValues.
  • New demos demonstrating new features etc.
    • demo_epinf, demonstrating the input dependent noise and signal variance model
    • demo_svi_regression, demo_svi_classification
    • demo_modelcomparison2, demo_survival_comparison

Several minor bugfixes


Logo Crino 1.0.0

by jlerouge - July 16, 2014, 17:54:55 CET [ Project Homepage BibTeX Download ] 197 views, 28 downloads, 1 subscription

About: Crino: a neural-network library based on Theano

Changes:

1.0.0 (7 july 2014) : - Initial release of crino - Implements a torch-like library to build artificial neural networks (ANN) - Provides standard implementations for : * auto-encoders * multi-layer perceptrons (MLP) * deep neural networks (DNN) * input output deep architecture (IODA) - Provides a batch-gradient backpropagation algorithm, with adaptative learning rate


Logo ABACOC Adaptive Ball Cover for Classification 1.0

by kikot - July 14, 2014, 16:27:03 CET [ BibTeX BibTeX for corresponding Paper Download ] 236 views, 41 downloads, 2 subscriptions

About: Online Action Recognition via Nonparametric Incremental Learning. Java and Matlab code already available. A Python version and the Java source code will be released soon.

Changes:

Initial release of the library, future changes will be advertised shortly.


Logo RankSVM NC 1.0

by rflamary - July 10, 2014, 15:51:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 287 views, 54 downloads, 1 subscription

About: This package is an implementation of a linear RankSVM solver with non-convex regularization.

Changes:

Initial Announcement on mloss.org.


Logo JMLR MSVMpack 1.5

by lauerfab - July 3, 2014, 16:02:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10093 views, 3534 downloads, 2 subscriptions

About: MSVMpack is a Multi-class Support Vector Machine (M-SVM) package. It is dedicated to SVMs which can handle more than two classes without relying on decomposition methods and implements the four M-SVM models from the literature: Weston and Watkins M-SVM, Crammer and Singer M-SVM, Lee, Lin and Wahba M-SVM, and the M-SVM2 of Guermeur and Monfrini.

Changes:
  • Windows binaries are now included (by Emmanuel Didiot)
  • MSVMpack can now be compiled on Windows (by Emmanuel Didiot)
  • Fixed polynomial kernel
  • Minor bug fixes

Logo JMLR Sally 0.9.0

by konrad - July 1, 2014, 22:43:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18092 views, 3666 downloads, 2 subscriptions

About: A Tool for Embedding Strings in Vector Spaces

Changes:

Support for hash-based dimension reduction: simhash, minhash and Bloom filter. Support for several n-gram variants: regular, sorted, positional and blended n-grams. Simplified configuration.


Logo FEAST 1.1.1

by apocock - June 30, 2014, 01:30:23 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13563 views, 3237 downloads, 1 subscription

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About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:
  • Bug fixes to memory management.
  • Compatibility changes for PyFeast python wrapper (note the C library now returns feature indices starting from 0, the Matlab wrapper still returns indices starting from 1).
  • Added C version of MIM.
  • Updated internal version of MIToolbox.

Logo MIToolbox 2.1

by apocock - June 30, 2014, 01:05:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11712 views, 2248 downloads, 1 subscription

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features.

Changes:

Added weighted entropy functions. Fixed a few memory handling bugs.


Logo JMLR Information Theoretical Estimators 0.60

by szzoli - June 3, 2014, 00:17:33 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 40658 views, 8814 downloads, 2 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.

Changes:
  • Quick test on the Tsallis divergence: introduced.

  • Pearson chi square divergence estimation in the exponential family (MLE + analytical formula): added.


Logo A Pattern Recognizer In Lua with ANNs v0.3.1

by pakozm - May 30, 2014, 10:49:10 CET [ Project Homepage BibTeX Download ] 1906 views, 443 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 GradMC 2.00

by tur - April 14, 2014, 15:48:48 CET [ BibTeX Download ] 1370 views, 479 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 Social Impact theory based Optimizer library 1.0.2

by rishem - March 24, 2014, 08:29:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2392 views, 569 downloads, 1 subscription

About: This is an optimization library based on Social Impact Theory(SITO). The optimizer works in the same way as PSO and GA.

Changes:

A new variant 'Continuous Opinion Dynamics Optimizer (CODO)' has been implemented in this version. Minor changes in implementation of objective function.


Logo minFunc 2012

by markSchmidt - December 18, 2013, 01:07:07 CET [ Project Homepage BibTeX Download ] 782 views, 157 downloads, 1 subscription

About: minFunc is a Matlab function for unconstrained optimization of differentiable real-valued multivariate functions using line-search methods. It uses an interface very similar to the Matlab Optimization Toolbox function fminunc, and can be called as a replacement for this function. On many problems, minFunc requires fewer function evaluations to converge than fminunc (or minimize.m). Further it can optimize problems with a much larger number of variables (fminunc is restricted to several thousand variables), and uses a line search that is robust to several common function pathologies.

Changes:

Initial Announcement on mloss.org.


Logo JMLR GPML Gaussian Processes for Machine Learning Toolbox 3.4

by hn - November 11, 2013, 14:46:52 CET [ Project Homepage BibTeX Download ] 17094 views, 4194 downloads, 3 subscriptions

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About: The GPML toolbox is a flexible and generic Octave 3.2.x and Matlab 7.x implementation of inference and prediction in Gaussian Process (GP) models.

Changes:
  • derivatives w.r.t. inducing points xu in infFITC, infFITC_Laplace, infFITC_EP so that one can treat the inducing points either as fixed given quantities or as additional hyperparameters
  • new GLM likelihood likExp for inter-arrival time modeling
  • new GLM likelihood likWeibull for extremal value regression
  • new GLM likelihood likGumbel for extremal value regression
  • new mean function meanPoly depending polynomially on the data
  • infExact can deal safely with the zero noise variance limit
  • support of GP warping through the new likelihood function likGaussWarp

About: The glm-ie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glm-ie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some MEX files. The code is fully compatible to both Matlab 7.x and GNU Octave 3.2.x. Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework allowing for both MAP estimation and approximate Bayesian inference.

Changes:

added factorial mean field inference as a third algorithm complementing expectation propagation and variational Bayes

generalised non-Gaussian potentials so that affine instead of linear functions of the latent variables can be used


Logo Chalearn gesture challenge code by jun wan 1.0

by joewan - September 11, 2013, 07:32:51 CET [ BibTeX BibTeX for corresponding Paper Download ] 1900 views, 449 downloads, 0 subscriptions

About: This code is provided by Jun Wan. It is used in the Chalearn one-shot learning gesture challenge (round 2). This code includes: bag of features, 3D MoSIFT, EMoSIFT and SMoSIFT features.

Changes:

Initial Announcement on mloss.org.


Logo Multilinear Principal Component Analysis 1.3

by hplu - September 8, 2013, 13:04:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3383 views, 653 downloads, 1 subscription

About: A Matlab implementation of Multilinear PCA (MPCA) and MPCA+LDA for dimensionality reduction of tensor data with sample code on gait recognition

Changes:
  1. The MPCA paper is updated with a typo (the MAD measure in Table II) corrected.

  2. Tensor toolbox version 2.1 is included for convenience.

  3. Full code on gait recognition is included for verification and comparison.


About: Toeblitz is a MATLAB/Octave package for operations on positive definite Toeplitz matrices. It can solve Toeplitz systems Tx = b in O(n*log(n)) time and O(n) memory, compute matrix inverses T^(-1) (with free log determinant) in O(n^2) time and memory, compute log determinants (without inverses) in O(n^2) time and O(n) memory, and compute traces of products A*T for any matrix A, in minimal O(n^2) time and memory.

Changes:

Adding tar directly instead of via link


About: Stochastic neighbor embedding originally aims at the reconstruction of given distance relations in a low-dimensional Euclidean space. This can be regarded as general approach to multi-dimensional scaling, but the reconstruction is based on the definition of input (and output) neighborhood probability alone. The present implementation also allows for handling dissimilarity or score-induced neighborhood topologies and makes use of quasi 2nd order gradient-based (l-)BFGS optimization.

Changes:
  • gradient in xsne_fun.m fixed! (constant factor m was missing)

  • symmetry option re-introduced allowing for enabling symmetric and asymmetric versions of SNE and t-SNE


Logo cbMDS Correlation Based Multi Dimensional Scaling 1.2

by emstrick - July 27, 2013, 14:35:36 CET [ BibTeX BibTeX for corresponding Paper Download ] 2719 views, 760 downloads, 1 subscription

About: The aim is to embed a given data relationship matrix into a low-dimensional Euclidean space such that the point distances / distance ranks correlate best with the original input relationships. Input relationships may be given as (sparse) (asymmetric) distance, dissimilarity, or (negative!) score matrices. Input-output relations are modeled as low-conditioned. (Weighted) Pearson and soft Spearman rank correlation, and unweighted soft Kendall correlation are supported correlation measures for input/output object neighborhood relationships.

Changes:
  • Initial release (Ver 1.0): Weighted Pearson and correlation and soft Spearman rank correlation, Tue Dec 4 16:14:51 CET 2012

  • Ver 1.1 Added soft Kendall correlation, Fri Mar 8 08:41:09 CET 2013

  • Ver 1.2 Added reconstruction of sparse relationship matrices, Fri Jul 26 16:58:37 CEST 2013


Showing Items 1-20 of 64 on page 1 of 4: 1 2 3 4 Next