All entries.
Showing Items 81-90 of 579 on page 9 of 58: First Previous 4 5 6 7 8 9 10 11 12 13 14 Next Last

Logo AugmentedSVM 1.0.0

by ashukla - October 2, 2014, 11:24:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1172 views, 236 downloads, 2 subscriptions

About: A MATLAB toolkit for performing generalized regression with equality/inequality constraints on the function value/gradient.

Changes:

Initial Announcement on mloss.org.


Logo hca 0.61

by wbuntine - September 10, 2014, 03:33:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7793 views, 1403 downloads, 4 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrections to diagnostics and topic report. Correction to estimating alpha. Now estimating beta sometimes (when estimating phi).


Logo JMLR Darwin 1.8

by sgould - September 3, 2014, 08:42:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 34564 views, 7218 downloads, 4 subscriptions

About: A platform-independent C++ framework for machine learning, graphical models, and computer vision research and development.

Changes:

Version 1.8:

  • Added Superpixel Graph Label Transfer (nnGraph) Project project
  • Added Python scripts for automating some projects
  • Added ability to pre-process features on-the-fly with one drwnFeatureTransform when applying or learning another drwnFeatureTransform
  • Fixed race condition in Windows threading (thanks to Edison Guo)
  • Switched Windows and Linux to build against OpenCV 2.4.9
  • Changed drwnMAPInference::inference to return upper and lower energy bounds
  • Added pruneRounds function to drwnBoostedClassifier
  • Added drwnSLICSuperpixels function
  • Added drwnIndexQueue class
  • mexLearnClassifier and mexAnalyseClassifier now support integer label types
  • Bug fix in mexSaveSuperpixels to support single channel

Logo r-cran-e1071 1.6-4

by r-cran-robot - September 1, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 15997 views, 3397 downloads, 1 subscription

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
(based on 1 vote)

About: Misc Functions of the Department of Statistics (e1071), TU Wien

Changes:

Fetched by r-cran-robot on 2015-05-01 00:00:04.666842


Logo RLPy 1.3a

by bobklein2 - August 28, 2014, 14:34:35 CET [ Project Homepage BibTeX Download ] 2716 views, 620 downloads, 1 subscription

About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:
  • Fixed bug where results using same random seed were different with visualization turned on/off
  • Created RLPy package on pypi (Available at https://pypi.python.org/pypi/rlpy)
  • Switched from custom logger class to python default
  • Added unit tests
  • Code readability improvements (formatting, variable names/ordering)
  • Restructured TD Learning heirarchy
  • Updated tutorials

Logo r-cran-bigRR 1.3-10

by r-cran-robot - August 23, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 1809 views, 471 downloads, 0 subscriptions

About: Generalized Ridge Regression (with special advantage for p >> n cases)

Changes:

Fetched by r-cran-robot on 2015-05-01 00:00:04.045375


Logo Salad 0.5.0

by chwress - August 22, 2014, 17:54:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5685 views, 1048 downloads, 1 subscription

About: A Content Anomaly Detector based on n-Grams

Changes:

Lots and lots of cool new features and bugfixes ;)

  • Refinements to the user interface: This includes a progress indicator, colors, etc.
  • Determine the expected error (salad-inspect)
  • Enable the user to echo the used parametrization: salad [train|predict|inspect] --echo-params
  • Allow to set the input batch size as program argument: salad [train|predict|inspect] --batch-size
  • libsalad: The library allows to access salad's basic functions
  • Installers and precompiled binaries: Windows installer, Debian (ppa:chwress/salad) & RPM packages as well a generic linux installers.
  • Various minor bug fixes
  • Support for "length at end" zip files
  • Improve salad's usage in a 2-class setting: salad [train|predict|inspect] --input-filter

Logo CURFIL 1.1

by hanschul - August 18, 2014, 13:54:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1019 views, 239 downloads, 1 subscription

About: CURFIL uses NVIDIA CUDA to accelerate random forest training and prediction for RGB and RGB-D images. It focuses on image labelling tasks, such as image segmentation or classification applications. CURFIL allows to search for optimal hyper-parameter configurations (e.g. using the hyperopt) package) by massively decreasing training time.

Changes:

Initial Announcement on mloss.org.


Logo Toeblitz Toolkit for Fast Toeplitz Matrix Operations 1.03

by cunningham - August 13, 2014, 02:21:36 CET [ BibTeX Download ] 3415 views, 883 downloads, 2 subscriptions

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 a write-up in written/toeblitz.pdf describing the package.


Logo Caffe 0.9999

by sergeyk - August 9, 2014, 01:57:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5771 views, 969 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


Showing Items 81-90 of 579 on page 9 of 58: First Previous 4 5 6 7 8 9 10 11 12 13 14 Next Last