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CIRG - Research  -  Neural Networks 



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OVERVIEW

The focus of the neural networks group is to investigate aspects of training and optimization of neural networks, and to apply neural networks to solve real-world problems. The activities of this focus area are mainly centered around architecture selection, active learning, and the development of new an efficient training algorithms. Some work is done on self-organizing maps.

Current applications are directed towards data mining, spam detection, user authentication, fraud detection, gesture recognition, and trading on financial markets. Applications of self-organization maps to exploratory data analysis, data mining, and species identification are done.

ACTIVE MEMBERS

List the current members actively doing research in this focus area. [ Show ]

ALUMNI MEMBERS

S van der Stockt

M.Sc Completed in 2008

E Dean

M.Sc Started in 2002

J Pun

M.Sc Completed

E Clements

Hons-B.Sc Completed in 2003

U Paquet

M.Sc Completed in 2003

R van den Hoven

Hons-B.Sc Completed in 2003

A Ismail

PhD Started in 2005
M.Sc Completed in 2001

A Adejumo

M.Sc Completed in 1999

GROUP PUBLICATIONS

List publications of this research focus area. [ Show ]

MEMBER PROFILE



 Name:

 Ulrich Paquet

Portrait photo

 E-mail:

 up208@cam.ac.uk

 Group(s):

 Swarm Intelligence
 Neural Networks

 

 Degree specific information: M.Sc

 Title:

 Training Support Vector Machines with Particle Swarms

 Abstract:

I am doing research on Particle Swarm Optimisation for optimising functions f(x) with linear equality constraints Ax = b, and linear inequality constraints. This is used to train Support Vector Machines. Training a SVM requires solving a quadratic programming program with dimension equal to the number of training examples. I am currently working on methods of decomposing the problem and optimising the smaller subproblems using the PSO developed for constrained optimisation.

 Supervisor / Co-Supervisor:

 AP Engelbrecht

 Thesis:

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