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Logo pymaBandits 1.0

by garivier - July 6, 2012, 18:32:41 CET [ BibTeX Download ] 15375 views, 2513 downloads, 1 subscription

About: This package contains a python and a matlab implementation of the most widely used algorithms for multi-armed bandit problems. The purpose of this package is to provide simple environments for comparison and numerical evaluation of policies.

Changes:

Initial Announcement on mloss.org.


Logo FABIA 2.8.0

by hochreit - October 18, 2013, 10:14:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15070 views, 3095 downloads, 1 subscription

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About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing.

Changes:

CHANGES IN VERSION 2.8.0

NEW FEATURES

o rescaling of lapla
o extractPlot does not plot sorted matrices

CHANGES IN VERSION 2.4.0

o spfabia bugfixes

CHANGES IN VERSION 2.3.1

NEW FEATURES

o Getters and setters for class Factorization

2.0.0:

  • spfabia: fabia for a sparse data matrix (in sparse matrix format) and sparse vector/matrix computations in the code to speed up computations. spfabia applications: (a) detecting >identity by descent< in next generation sequencing data with rare variants, (b) detecting >shared haplotypes< in disease studies based on next generation sequencing data with rare variants;
  • fabia for non-negative factorization (parameter: non_negative);
  • changed to C and removed dependencies to Rcpp;
  • improved update for lambda (alpha should be smaller, e.g. 0.03);
  • introduced maximal number of row elements (lL);
  • introduced cycle bL when upper bounds nL or lL are effective;
  • reduced computational complexity;
  • bug fixes: (a) update formula for lambda: tighter approximation, (b) corrected inverse of the conditional covariance matrix of z;

1.4.0:

  • New option nL: maximal number of biclusters per row element;
  • Sort biclusters according to information content;
  • Improved and extended preprocessing;
  • Update to R2.13

Logo KeBABS 1.4.1

by UBod - November 3, 2015, 11:33:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15066 views, 2735 downloads, 3 subscriptions

About: Kernel-Based Analysis of Biological Sequences

Changes:
  • new method to compute prediction profiles from models trained with mixture kernels
  • correction for position specific kernel with offsets
  • corrections for prediction profile of motif kernel
  • additional hint on help page of kbsvm

Logo r-cran-ipred 0.9-1

by r-cran-robot - November 14, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 15066 views, 3535 downloads, 1 subscription

About: Improved Predictors

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:05.613011


Logo OpenViBE 0.8.0

by k3rl0u4rn - October 1, 2010, 16:15:08 CET [ Project Homepage BibTeX Download ] 14852 views, 3983 downloads, 1 subscription

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About: OpenViBE is an opensource platform that enables to design, test and use Brain-Computer Interfaces (BCI). Broadly speaking, OpenViBE can be used in many real-time Neuroscience applications [...]

Changes:

New release 0.8.0.


Logo Circular Statistics Toolbox 2010c

by phb - June 9, 2010, 13:02:26 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14715 views, 1958 downloads, 1 subscription

About: Toolbox for circular statistics with Matlab (The Mathworks).

Changes:

Some bugfixes.


Logo Universal Java Matrix Package 0.3.0

by arndt - July 31, 2015, 14:23:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14694 views, 2783 downloads, 3 subscriptions

About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multi-threading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more.

Changes:

Updated to version 0.3.0


Logo SGD 2.0

by leonbottou - October 11, 2011, 20:59:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14629 views, 2281 downloads, 5 subscriptions

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About: The SGD-2.0 package contains implementations of the SGD and ASGD algorithms for linear SVMs and linear CRFs.

Changes:

Version 2.0 features ASGD.


Logo MALLET 2.0-rc4

by jacktanner - August 24, 2009, 23:10:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14609 views, 2432 downloads, 1 subscription

About: MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to [...]

Changes:

MALLET 2.0 RC4 Release Notes July 16, 2009

Major updates:

An implementation of generalized expectation criteria training of MaxEnt classifiers and methods for obtaining constraints (c.f. Gregory Druck, Gideon Mann, Andrew McCallum "Learning from Labeled Features using Generalized Expectation Criteria.")

PagedInstanceList has been substantially rewritten by Mike Bond.

Bug fixes to topic model hyperparameter optimization and topic inference.


Logo chi2 kernel 1.5

by gruel - February 15, 2009, 22:32:21 CET [ BibTeX Download ] 14543 views, 2716 downloads, 1 subscription

About: Very fast implementation of the chi-squared distance between histograms (or vectors with non-negative entries).

Changes:

Removed bug in symmetric chi-square distance and updated python wrapper to python 2.5 compatiblity.


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