Research: Parallel Computing for Machine Learning

Project Details

Project Lead
Wilson Rivera 
Project Manager
Wilson Rivera 
Project Members
Carlos Gomez, Oscar Gomez, Rogelio Vázquez, Jorge Perea, Henry Estepar, Andres Malines, Christian Montes, Juan Nieves, Omar Soto  
Supporting Experts
Saliya Ekanayake  
Institution
University of Puerto Rico, Electrical and Computer Emgineering Department  
Discipline
Computer Science (401) 
Subdiscipline
14.09 Computer Engineering 

Abstract

The goal of this project is to discover, understand, and exploit the available parallelism in machine learning algorithms as applied to big data problems.  

Intellectual Merit

explore parallel computing for machine learning by working on real problems and designing parallel machine learning algorithms

Broader Impacts

This project will provide invaluable research, educational and training opportunities to students at both undergraduate and graduate levels.

Scale of Use

About 10 research collaborators.