CloudDALVQ 1.0 released

CloudDALVQ is a scientific project for testing new large scale clustering/quantization algorithms. These algorithms are typically distributed and asynchronous. The code is written in C#/.NET (4.0) and runs on the Microsoft Azure Platform. The project is built using Lokad.Cloud which provides an O/C (Object to Cloud) Mapper and an 'execution framework' that leverages low level technicalities of MS Azure.

This project follows theoretical work done by Patra [1]. This project is also naturally linked to the first work of Durut and Rossi on Azure implementation of the popular batch KMeans algorithm


  1. BenoƮt Patra, "Convergence of distributed asynchronous learning vector quantization algorithms", Journal of Machine Learning Research, pp. 3431-3466, 2011.