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Logo OpenOpt 0.54

by Dmitrey - June 15, 2014, 14:50:37 CET [ Project Homepage BibTeX Download ] 42718 views, 8948 downloads, 3 subscriptions

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About: Universal Python-written numerical optimization toolbox. Problems: NLP, LP, QP, NSP, MILP, LSP, LLSP, MMP, GLP, SLE, MOP etc; general logical constraints, categorical variables, automatic differentiation, stochastic programming, interval analysis, many other goodies

Changes:

http://openopt.org/Changelog


Logo OpenViBE 0.8.0

by k3rl0u4rn - October 1, 2010, 16:15:08 CET [ Project Homepage BibTeX Download ] 10983 views, 3066 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 Optunity 0.2.0

by claesenm - July 24, 2014, 10:07:54 CET [ Project Homepage BibTeX Download ] 523 views, 168 downloads, 1 subscription

About: Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning tasks, both supervised and unsupervised.This package provides several distinct approaches to solve such problems including some helpful facilities such as cross-validation and a plethora of score functions.

Changes:

Initial Announcement on mloss.org.


Logo OptWok 0.3.1

by ong - May 2, 2013, 10:46:11 CET [ Project Homepage BibTeX Download ] 7094 views, 1361 downloads, 1 subscription

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier.

Changes:
  • minor bugfix

Logo Orange 2.6

by janez - February 14, 2013, 18:15:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11816 views, 2300 downloads, 1 subscription

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About: Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

Changes:

The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL.

Changed the BibTeX reference to the paper recently published in JMLR MLOSS.


Logo Ordinal Choquistic Regression 1.00

by AliFall - January 30, 2014, 15:42:34 CET [ BibTeX BibTeX for corresponding Paper Download ] 1025 views, 237 downloads, 1 subscription

About: "Ordinal Choquistic Regression" model using the maximum likelihood

Changes:

Initial Announcement on mloss.org.


Logo Output Kernel Learning 2.0

by posaune - March 22, 2012, 11:34:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4710 views, 752 downloads, 1 subscription

About: A Matlab script for learning vector-valued functions and kernels on the output space.

Changes:

Added code for learning low-rank output kernels.


Logo OXlearn 1.0

by gwestermann - January 11, 2010, 11:48:26 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4086 views, 850 downloads, 1 subscription

About: OXlearn is a free neural network simulation software that enables you to build, train, test and analyse connectionist neural network models. Because OXlearn is implemented as a Matlab toolbox you can run it on all operation systems (Windows, Linux, MAC, etc.), and there is a compiled version for XP.

Changes:

Initial Announcement on mloss.org.


About: PALMA computes the optimal spliced alignment of a mRNA sequence to a genomic sequence. The main python script takes two FASTA files containing the target (e.g. a DNA sequence, part of the genome) [...]

Changes:

Initial Announcement on mloss.org.


About: The package estimates the matrix of partial correlations based on different regularized regression methods: lasso, adaptive lasso, PLS, and Ridge Regression.

Changes:

Initial Announcement on mloss.org.


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