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Logo bob 1.2.2

by anjos - October 28, 2013, 14:37:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7081 views, 1562 downloads, 1 subscription

About: Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland.

Changes:

Bob 1.2.0 comes about 1 year after we released Bob 1.0.0. This new release comes with a big set of new features and lots of changes under the hood to make your experiments run even smoother. Some statistics:

Diff URL: https://github.com/idiap/bob/compare/v1.1.4...HEAD Commits: 629 Files changed: 954 Contributors: 7

Here is a quick list of things you should pay attention for while integrating your satellite packages against Bob 1.2.x:

  • The LBP module had its API changed look at the online docs for more details
  • LLRTrainer has been renamed to CGLogRegTrainer
  • The order in which you pass data to CGLogRegTrainer has been inverted (negatives now go first)
  • For C++ bindings, includes are in bob/python instead of bob/core/python
  • All specialized Bob exceptions are gone, if you were catching them, most have been cast into std::runtime_error's

For a detailed list of changes and additions, please look at our Changelog page for this release and minor updates:

https://github.com/idiap/bob/wiki/Changelog-from-1.1.4-to-1.2 https://github.com/idiap/bob/wiki/Changelog-from-1.2.0-to-1.2.1 https://github.com/idiap/bob/wiki/Changelog-from-1.2.1-to-1.2.2


Logo CVX, a modeling system for disciplined convex programming 1.2

by mcgrant - October 21, 2008, 23:55:08 CET [ Project Homepage BibTeX Download ] 7030 views, 1293 downloads, 2 subscriptions

About: CVX is a Matlab-based modeling system for convex optimization. CVX turns Matlab into a modeling language, allowing constraints and objectives to be specified using standard Matlab expression syntax. [...]

Changes:

Initial Announcement on mloss.org.


Logo libstb 1.8

by wbuntine - April 24, 2014, 09:02:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6995 views, 1362 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 ALGLIB 2.4.0

by Sergey_Bochkanov - March 10, 2010, 14:07:35 CET [ Project Homepage BibTeX Download ] 6995 views, 1607 downloads, 2 subscriptions

About: ALGLIB is an open source numerical analysis library distributed under GPL 2+. It implements both general numerical algorithms and machine learning algorithms. ALGLIB can be used from C#, C++, FreePascal, VBA and other languages. It is the only numerical analysis library which uses automatic translation to generate source code written in different programming languages with 100% identical functionality.

Changes:
  1. New algorithms implemented: exact and approximate nearest neighbor search using kd-trees, new multidimensional scattered data interpolation/fitting algorithm with O(N·logN) complexity (modified Shepard's method with fast k-NN queries), linear algebra algorithms

  2. faster QR/LQ, matrix inversion, condition number estimation.

  3. Minor fixes


Logo MinorThird 20080414

by frank - June 9, 2008, 09:08:30 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6951 views, 2007 downloads, 1 subscription

About: MinorThird is a collection of Java classes for storing text, annotating text, and learning to extract entities and categorize text. It was written primarily by William W. Cohen, a professor at [...]

Changes:

Initial Announcement on mloss.org.


Logo K tree 0.4.2

by cdevries - July 4, 2011, 06:01:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6940 views, 1508 downloads, 1 subscription

About: The K-tree is a scalable approach to clustering inspired by the B+-tree and k-means algorithms.

Changes:

Release of K-tree implementation in Python. This is targeted at a research and rapid prototyping audience.


Logo r-cran-gbm 2.0-8

by r-cran-robot - January 17, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 6927 views, 1369 downloads, 1 subscription

About: Generalized Boosted Regression Models

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:05.019963


Logo Experiment Databases for Machine Learning 0.1

by JoaquinVanschoren - October 7, 2008, 18:06:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6856 views, 1109 downloads, 1 subscription

About: Experiment Databases for Machine Learning is a large public database of machine learning experiments as well as a framework for producing similar databases for specific goals. It provides a way to [...]

Changes:

Initial Announcement on mloss.org.


Logo Caffe 0.9999

by sergeyk - August 9, 2014, 01:57:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6777 views, 1121 downloads, 2 subscriptions

About: Caffe aims to provide computer vision scientists with a clean, modifiable implementation of state-of-the-art deep learning algorithms. We believe that Caffe is the fastest available GPU CNN implementation. Caffe also provides seamless switching between CPU and GPU, which allows one to train models with fast GPUs and then deploy them on non-GPU clusters. Even in CPU mode, computing predictions on an image takes only 20 ms (in batch mode).

Changes:

LOTS of stuff: https://github.com/BVLC/caffe/releases/tag/v0.9999


Logo multi assignment clustering of Boolean data 2.001

by mafrank - March 3, 2012, 09:04:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6750 views, 945 downloads, 1 subscription

About: Implementation of the multi-assignment clustering method for Boolean vectors.

Changes:

new bib added


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