Search Results for "open-shell" - Page 2

Implementation of duration high-order hidden Markov model (DHO-HMM) in Matlab with application in speech recognition.

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...

MCTIMME is a nonparametric Bayesian computational framework for analyzing microbial time-series data.The current implementation is in Matlab.

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.

A feature selection and classification algorithm. It is based on L1 Norm Support Vector Machine with t-test and Recursive Feature Elimination.

This is a Matlab software package for single molecule FRET data analysis.

Computer Vision Application.

The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy...

DHAC distribution

This project is devoted to the creation of an open source Error-Correcting Output Codes (ECOC) library for the Machine Learning community. The ECOC framework is a powerful tool to deal with multi-class categorization problems.

DOGMA is a MATLAB toolbox for discriminative online learning. It implements all the state of the art algorithms in a unique and simple framework. Examples are Perceptron, Passive-Aggresive, ALMA, NORMA, SILK, Projectron, RBP, Banditron, etc.

Content-based Image Retrieval (CBIR) consists of retrieving visually similar images to a given query image from a database of images. It is done by comparing selected visual features such as color, texture and shape from the image database.

Octave program which trains artificial neural networks to play backgammon through self-play.

This project applies an interpretation of a k-NN algorithm to a library of GPS commuter data for speed prediction. The overall goal is to lay the foundation for a power management protocol for use in electric vehicles with hybrid energy storage.

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.

This project contains code for evaluation of reflection symmetry detection algorithms

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.

A MATLAB spectral clustering package to handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. We implement various ways of approximating the dense similarity matrix, including nearest neighbors and the Nystrom method.

The project goal is to develop several IP cores that would implement artificial neural networks using FPGA resources. These cores will be designed in such a way to allow easy integration in the Xilinx EDK framework.

Linear Time Invariant (LTI) system identification using particle swarm optimization (PSO) algorithm. Creators : Vahid Kiani, Hadi Sadoghi Yazdi

...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.