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Logo Semi Stochastic Gradient Descent 1.0

by konkey - July 9, 2014, 04:28:47 CET [ BibTeX BibTeX for corresponding Paper Download ] 1721 views, 461 downloads, 1 subscription

About: Efficient implementation of Semi-Stochastic Gradient Descent algorithm (S2GD) for training logistic regression (L2-regularized).

Changes:

Initial Announcement on mloss.org.


About: This provide a semi-supervised learning method based co-training for RGB-D object recognition. Besides, we evaluate four state-of-the-art feature learing method under the semi-supervised learning framework.

Changes:

Initial Announcement on mloss.org.


Logo SenseClusters 1.01

by tpederse - August 12, 2008, 16:39:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6735 views, 1947 downloads, 1 subscription

About: SenseClusters is a package of (mostly) Perl programs that allows a user to cluster similar contexts together using unsupervised knowledge-lean methods. These techniques have been applied to word [...]

Changes:

Initial Announcement on mloss.org.


Logo seqan 1.2

by sonne - November 2, 2009, 14:54:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7142 views, 1363 downloads, 1 subscription

About: SeqAn is an open source C++ library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data.

Changes:
  • 5 more applications, i.e. DFI, MicroRazerS, PairAlign, SeqCons, TreeRecon
  • stable release of RazerS supporting paired-end read mapping and configurable sensitivity
  • new alignment algorithms, e.g. banded, configurable alignments (overlap, semi-global, ...)
  • realignment algorithm
  • NGS data structures and formats, e.g. SAM, Amos, ...
  • new alphabets, e.g. Dna with base call qualities, profile characters
  • auxiliary data structures and algorithms, e.g. double ended queue, command line parser
  • positional scores
  • CMake support

Logo Sequin v1.1.0.0

by apitman - September 23, 2011, 11:47:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4786 views, 1148 downloads, 1 subscription

About: Sequin is an open source sequence mining library written in C#.

Changes:

Sequin v1.1.0.0 released


Logo SFPD 1

by zenog - September 21, 2011, 14:26:45 CET [ Project Homepage BibTeX Download ] 2249 views, 566 downloads, 1 subscription

About: Survival forests: Random Forests variant for survival analysis. Original implementation by Leo Breiman.

Changes:

Initial Announcement on mloss.org.


Logo SGD 2.0

by leonbottou - October 11, 2011, 20:59:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11730 views, 1870 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 JMLR Shark 2.3.0

by igel - October 24, 2009, 22:12:48 CET [ Project Homepage BibTeX Download ] 28080 views, 5585 downloads, 1 subscription

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About: SHARK is a modular C++ library for the design and optimization of adaptive systems. It provides various machine learning and computational intelligence techniques.

Changes:
  • new build system
  • minor bug fixes

Logo JMLR SHOGUN 4.0.0

by sonne - February 5, 2015, 09:09:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 96397 views, 13575 downloads, 6 subscriptions

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About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line.

Changes:

This release features the work of our 8 GSoC 2014 students [student; mentors]:

  • OpenCV Integration and Computer Vision Applications [Abhijeet Kislay; Kevin Hughes]
  • Large-Scale Multi-Label Classification [Abinash Panda; Thoralf Klein]
  • Large-scale structured prediction with approximate inference [Jiaolong Xu; Shell Hu]
  • Essential Deep Learning Modules [Khaled Nasr; Sergey Lisitsyn, Theofanis Karaletsos]
  • Fundamental Machine Learning: decision trees, kernel density estimation [Parijat Mazumdar ; Fernando Iglesias]
  • Shogun Missionary & Shogun in Education [Saurabh Mahindre; Heiko Strathmann]
  • Testing and Measuring Variable Interactions With Kernels [Soumyajit De; Dino Sejdinovic, Heiko Strathmann]
  • Variational Learning for Gaussian Processes [Wu Lin; Heiko Strathmann, Emtiyaz Khan]

It also contains several cleanups and bugfixes:

Features

  • New Shogun project description [Heiko Strathmann]
  • ID3 algorithm for decision tree learning [Parijat Mazumdar]
  • New modes for PCA matrix factorizations: SVD & EVD, in-place or reallocating [Parijat Mazumdar]
  • Add Neural Networks with linear, logistic and softmax neurons [Khaled Nasr]
  • Add kernel multiclass strategy examples in multiclass notebook [Saurabh Mahindre]
  • Add decision trees notebook containing examples for ID3 algorithm [Parijat Mazumdar]
  • Add sudoku recognizer ipython notebook [Alejandro Hernandez]
  • Add in-place subsets on features, labels, and custom kernels [Heiko Strathmann]
  • Add Principal Component Analysis notebook [Abhijeet Kislay]
  • Add Multiple Kernel Learning notebook [Saurabh Mahindre]
  • Add Multi-Label classes to enable Multi-Label classification [Thoralf Klein]
  • Add rectified linear neurons, dropout and max-norm regularization to neural networks [Khaled Nasr]
  • Add C4.5 algorithm for multiclass classification using decision trees [Parijat Mazumdar]
  • Add support for arbitrary acyclic graph-structured neural networks [Khaled Nasr]
  • Add CART algorithm for classification and regression using decision trees [Parijat Mazumdar]
  • Add CHAID algorithm for multiclass classification and regression using decision trees [Parijat Mazumdar]
  • Add Convolutional Neural Networks [Khaled Nasr]
  • Add Random Forests algorithm for ensemble learning using CART [Parijat Mazumdar]
  • Add Restricted Botlzmann Machines [Khaled Nasr]
  • Add Stochastic Gradient Boosting algorithm for ensemble learning [Parijat Mazumdar]
  • Add Deep contractive and denoising autoencoders [Khaled Nasr]
  • Add Deep belief networks [Khaled Nasr]

Bugfixes

  • Fix reference counting bugs in CList when reference counting is on [Heiko Strathmann, Thoralf Klein, lambday]
  • Fix memory problem in PCA::apply_to_feature_matrix [Parijat Mazumdar]
  • Fix crash in LeastAngleRegression for the case D greater than N [Parijat Mazumdar]
  • Fix memory violations in bundle method solvers [Thoralf Klein]
  • Fix fail in library_mldatahdf5.cpp example when http://mldata.org is not working properly [Parijat Mazumdar]
  • Fix memory leaks in Vowpal Wabbit, LibSVMFile and KernelPCA [Thoralf Klein]
  • Fix memory and control flow issues discovered by Coverity [Thoralf Klein]
  • Fix R modular interface SWIG typemap (Requires SWIG >= 2.0.5) [Matt Huska]

Cleanup and API Changes

  • PCA now depends on Eigen3 instead of LAPACK [Parijat Mazumdar]
  • Removing redundant and fixing implicit imports [Thoralf Klein]
  • Hide many methods from SWIG, reducing compile memory by 500MiB [Heiko Strathmann, Fernando Iglesias, Thoralf Klein]

Logo SIFT Extractor 1.0.0

by openpr_nlpr - December 2, 2011, 05:18:35 CET [ Project Homepage BibTeX Download ] 1609 views, 537 downloads, 1 subscription

About: This program is used to extract SIFT points from an image.

Changes:

Initial Announcement on mloss.org.


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