Search Results for "c-support.vim"

* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc

This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package

Research on automatic face recognition in images has rapidly developed into several inter-related lines, and this research has both lead to and been driven by a disparate and expanding set of commercial applications. The large number of research activities is evident in the growing number of scientific communications published on subjects related to face processing and recognition. Index Terms: face, recognition, eigenfaces, eigenvalues, eigenvectors, Karhunen-Loeve algorithm.

Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite: [1] Sethu...

ECOC PAK is a C++ Library for the Error Correcting Output Codes classification framework. It supports several coding and decoding strategies as well as several classifiers.

Computer Vision Application.

DHAC distribution

An adaptive neural network and evolutionary algorithms approach to the machine learning tasks, based on the modular graph grammars. Tested on the "two spirals problem" and other tasks. Implemented in Matlab and C++.

An implementation of a new proposed model of smoothly spiking neural networks + a fully analytical gradient descent algorithm.

A graphical MatLab framework for estimating the parameters of, modeling and simulating static and dynamic linear and polynomial systems in the errors-in-variables context with the intent of comparing various estimation strategies.

GURLS - (Grand Unified Regularized Least Squares) is a software package for training multiclass classifiers based on the Regularized Least Squares (RLS) loss function. The initial version has been designed and implemented in Matlab. Teh current goal is to implement an object-oriented C++ version to allow for a wider distribution of the library within the open-source developers' comunity. Main functionalities already implemented are: * Automatic parameter selection. * Handle massive datasets. * Great modularity, each method can be used independently. * Wide range of optimization routine. Please contact us if you want to join the developers' team or, otherwirse, feel free to download and use the library in your code and send us feedbacks about existing bugs, possible improvements and further developments.