3 projects found that use the lgpl version 3 or later license.


Logo libcmaes 0.8.1

by beniz - August 12, 2014, 16:18:31 CET [ Project Homepage BibTeX Download ] 724 views, 140 downloads, 2 subscriptions

About: Libcmaes is a multithreaded C++11 library for high performance blackbox stochastic optimization using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability.

Changes:
  • Added customization of data to file streaming function, ref #51
  • Added configure control for compiling the library alone without examples or tools, ref #11
  • Fixed code in order to avoid various compiler warnings
  • Fixed sample code in README, ref #54
  • Fixed get_max_iter and set_mt_feval in Parameters object
  • New CMAParameters constructor, from x0 as a vector of double
  • Updated building instructions for Mac OSX
  • New set_str_algo in Parameters object

Logo Crino 1.0.0

by jlerouge - July 16, 2014, 17:54:55 CET [ Project Homepage BibTeX Download ] 423 views, 78 downloads, 2 subscriptions

About: Crino: a neural-network library based on Theano

Changes:

1.0.0 (7 july 2014) : - Initial release of crino - Implements a torch-like library to build artificial neural networks (ANN) - Provides standard implementations for : * auto-encoders * multi-layer perceptrons (MLP) * deep neural networks (DNN) * input output deep architecture (IODA) - Provides a batch-gradient backpropagation algorithm, with adaptative learning rate


Logo MIToolbox 2.1

by apocock - June 30, 2014, 01:05:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12454 views, 2382 downloads, 1 subscription

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features.

Changes:

Added weighted entropy functions. Fixed a few memory handling bugs.