| EPSRC Reference: |
GR/L15388/01 |
| Title: |
ADAPTIVE RADIAL BASIS FUNCTION NETWORKS |
| Principal Investigator: |
Hallam, Professor J |
| Other Investigators: |
|
| Researcher Co-Investigators: |
|
| Project Partners: |
|
| Department: |
Sch of Informatics |
| Organisation: |
University of Edinburgh |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 May 1996 |
Ends: |
30 June 1999 |
Value (£): |
205,849
|
| EPSRC Research Topic Classifications: |
|
| EPSRC Industrial Sector Classifications: |
| Financial Services |
Information Technologies |
|
| Related Grants: |
|
| Panel History: |
|
|
Summary on Grant Application Form |
|
We propose to design, implement and evaluate local adaptation in radial basis function networks for supervised learning problems. This will build on previous work where we have shown the benefits of locally adapting the smoothness of the network output and lead to methods for adapting basis function sizes as well. We intend to explore ideas for local computation in order to improve learning speed. Extensive experiments are planned to test the performance of adaptive RBF networks relative to other algorithms on a wide range of problems, including many industrially relevant ones.
|
|
Key Findings |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Potential use in non-academic contexts |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Impacts |
|
| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
|
| Date Materialised |
|
|
|
|
Sectors submitted by the Researcher |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
| Project URL: |
|
| Further Information: |
|
| Organisation Website: |
http://www.ed.ac.uk |