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Logo SAMOA 0.0.1

by gdfm - April 2, 2014, 17:09:08 CET [ Project Homepage BibTeX Download ] 1495 views, 439 downloads, 1 subscription

About: SAMOA is a platform for mining big data streams. It is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms.


Initial Announcement on

Logo JMLR MultiBoost 1.2.02

by busarobi - March 31, 2014, 16:13:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 32308 views, 5465 downloads, 1 subscription

About: MultiBoost is a multi-purpose boosting package implemented in C++. It is based on the multi-class/multi-task AdaBoost.MH algorithm [Schapire-Singer, 1999]. Basic base learners (stumps, trees, products, Haar filters for image processing) can be easily complemented by new data representations and the corresponding base learners, without interfering with the main boosting engine.


Major changes :

  • The “early stopping” feature can now based on any metric output with the --outputinfo command line argument.

  • Early stopping now works with --slowresume command line argument.

Minor fixes:

  • More informative output when testing.

  • Various compilation glitch with recent clang (OsX/Linux).

Logo JMLR EnsembleSVM 2.0

by claesenm - March 31, 2014, 08:06:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9534 views, 3359 downloads, 2 subscriptions

About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks.


The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:

  1. Support for multithreading in training and prediction with ensemble models. Since both of these are embarassingly parallel, this has induced a significant speedup (3-fold on quad-core).
  2. Extensive programming framework for aggregation of base model predictions which allows highly efficient prototyping of new aggregation approaches. Additionally we provide several predefined strategies, including (weighted) majority voting, logistic regression and nonlinear SVMs of your choice -- be sure to check out the esvm-edit tool! The provided framework also allows you to efficiently program your own, novel aggregation schemes.
  3. Full code transition to C++11, the latest C++ standard, which enabled various performance improvements. The new release requires moderately recent compilers, such as gcc 4.7.2+ or clang 3.2+.
  4. Generic implementations of convenient facilities have been added, such as thread pools, deserialization factories and more.

The API and ABI have undergone significant changes, many of which are due to the transition to C++11.

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 ] 5381 views, 1217 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.


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

Logo Chordalysis 1.0

by fpetitjean - March 24, 2014, 01:22:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2039 views, 477 downloads, 1 subscription

About: Log-linear analysis for high-dimensional data


Initial Announcement on

Logo JMLR fastclime 1.2.3

by colin1898 - March 10, 2014, 08:54:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3527 views, 953 downloads, 1 subscription

About: The package "fastclime" provides a method of recover the precision matrix efficiently by applying parametric simplex method. The computation is based on a linear optimization solver. It also contains a generic LP solver and a parameterized LP solver using parametric simplex method.


Initial Announcement on

Logo MOSIS 0.55

by claasahl - March 9, 2014, 17:35:40 CET [ BibTeX Download ] 4577 views, 1520 downloads, 2 subscriptions

About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications.

  • Move "flow"-related classes into package "de.claas.mosis.flow" (e.g. Node and Link).
  • Refined and improved "flow"-related tests (e.g. Iterator and Node tests).
  • Refactored tests for data formats (e.g. PlainText and JSON tests).
  • Added visitor design pattern for graph-based functions (e.g. initialization and processing).
  • Documented parameters of Processor implementations.

Logo HierLearning 1.0

by neville - March 2, 2014, 04:24:37 CET [ BibTeX BibTeX for corresponding Paper Download ] 1845 views, 531 downloads, 1 subscription

About: HierLearning is a C++11 implementation of a general-purpose, multi-agent, hierarchical reinforcement learning system for sequential decision problems.


Initial Announcement on

Logo DAL 1.1

by ryota - February 18, 2014, 19:07:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16515 views, 2759 downloads, 1 subscription

About: DAL is an efficient and flexibible MATLAB toolbox for sparse/low-rank learning/reconstruction based on the dual augmented Lagrangian method.

  • Supports weighted lasso (dalsqal1.m, dallral1.m)
  • Supports weighted squared loss (dalwl1.m)
  • Bug fixes (group lasso and elastic-net-regularized logistic regression)

Logo JMLR BudgetedSVM v1.1

by nemanja - February 12, 2014, 20:53:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3000 views, 628 downloads, 1 subscription

About: BudgetedSVM is an open-source C++ toolbox for scalable non-linear classification. The toolbox can be seen as a missing link between LibLinear and LibSVM, combining the efficiency of linear with the accuracy of kernel SVM. We provide an Application Programming Interface for efficient training and testing of non-linear classifiers, supported by data structures designed for handling data which cannot fit in memory. We also provide command-line and Matlab interfaces, providing users with an efficient, easy-to-use tool for large-scale non-linear classification.


Changed license from LGPL v3 to Modified BSD.

Showing Items 161-170 of 604 on page 17 of 61: First Previous 12 13 14 15 16 17 18 19 20 21 22 Next Last