Departmental Colloquium (10/15/2010 Friday 1:30 pm, Department
Dr. Nagabhushan N. Tagadur
Professor and Chairman
Department of Information Science and Engineering
S.J. College of Engineering (affiliated with Visveshwaraya Technological
Radial Basis Function (RBF) neural networks have emerged as an
alternative to multilayer proceptron neural networks for classification
and function approximation. There has been a greater interest among
researchers to evolve RBF architectures dynamically during the learning
phase for a given application . Many significant works have appeared in
the literature on building efficient auto-configuring RBF networks
(Moody and Darken 1989, Platt 1991, Fritzke 1995, Chitra 2002, Wallace
2005, and many more). While synthesizing an RBF network during learning,
there is a need to look into certain objectives such as:
* The network must be compact.
* The network have good generalization.
* The network must learn fast.
This talk addresses some novel ideas such as:
* Positioning the RBF kernels at an optimal location in the input
* Pruning for any redundant neurons
* Computation of the width of RBF kernels based on edge information
* Training the network with only ”significant patterns”
while achieving the above objectives. Experiments have been conducted on
five benchmark data sets from the UCI machine learning repository and
the results are compared.
About the Speaker: Dr. Nagabhushan N. Tagadur holds masters and doctoral
degrees from the Indian Institute of Science, Bangalore, India. He has
been working with S.J. College of engineering, Mysore, India, since
1984. He was a visiting professor at Korea University, Seoul, in 2007
and Hannan University, Japan, in 2004. He has supervised five doctoral
theses and has over 40 publications in conferences and journals. He has
delivered a number of invited talks. Dr. Nagabhushan also served as the
head of the e-learning center of Visveswvaraya Technological University
(VTU) from January 2007 to August 2010. He is a reviewer for many
journals and has chaired many conferences.
Dr. Nagabhushan’s research areas include dynamic learning algorithms for
neural networks and the Industrial application of neural networks for
automobiles and in communication networks. He is a member of the
Institution of Engineers (India), the Indian Society for Technical
Education, and the Computer Society of India. He has a research
collaboration with mobile giant Nokia on local language support for