Fast Learning Neural Nets with Adaptive Learning Styles

Conference paper


Palmer-Brown, Dominic, Lee, S., Tepper, Jonathan and Roadknight, Chris 2003. Fast Learning Neural Nets with Adaptive Learning Styles.
AuthorsPalmer-Brown, Dominic, Lee, S., Tepper, Jonathan and Roadknight, Chris
TypeConference paper
Abstract

There are many learning methods in artificial neural networks. Depending on the application, one
learning or weight update rule may be more suitable than another, but the choice is not always clear-cut, despite
some fundamental constraints, such as whether the learning is supervised or unsupervised. This paper addresses
the learning style selection problem by proposing an adaptive learning style. Initially, some observations
concerning the nature of adaptation and learning are discussed in the context of the underlying motivations for
the research, and this paves the way for the description of an example system. The approach harnesses the
complementary strengths of two forms of learning which are dynamically combined in a rapid form of
adaptation that balances minimalist pattern intersection learning with Learning Vector Quantization. Both
methods are unsupervised, but the balance between the two is determined by a performance feedback parameter.
The result is a data-driven system that shifts between alternative solutions to pattern classification problems
rapidly when performance is poor, whilst adjusting to new data slowly, and residing in the vicinity of a solution
when performance is good.

Keywordsneural networks; fast learning; performance feedback; adaptive learning styles
Year2003
Accepted author manuscript
License
CC BY-ND
Publication dates
PrintJun 2003
Publication process dates
Deposited29 Apr 2010
Web address (URL)http://ducati.doc.ntu.ac.uk/uksim/ESM2003/Papers/Track-AI/AI-13/paper%20CR.pdf
http://hdl.handle.net/10552/772
Additional information

Citation:
Palmer-Brown, D. et al. (2003). “Fast Learning Neural Nets with Adaptive Learning Styles.” (Invited Paper). In Proceedings of the 17th European Simulation Multiconference (ESM'2003) Nottingham Trent University, Nottingham, UK, 9th - 11th June, pp. 118–123..

Permalink -

https://repository.uel.ac.uk/item/868z8

Download files


Accepted author manuscript
  • 133
    total views
  • 60
    total downloads
  • 2
    views this month
  • 0
    downloads this month

Export as

Related outputs

Cyber Threat Predictive Analytics for Improving Cyber Supply Chain Security
Yeboah-Ofori, A., Islam, S., Lee, S. W., Shamszaman, Z. U., Muhammad, K., Altaf, M. and Al-Rakhami, M. S. 2021. Cyber Threat Predictive Analytics for Improving Cyber Supply Chain Security. IEEE Access. 9, pp. 94318-94337. https://doi.org/10.1109/ACCESS.2021.3087109
Activities of daily life recognition using process representation modelling to support intention analysis
Naeem, U., Bashroush, R., Anthony, Richard, Azam, Muhammad Awais, Tawil, Abdel Rahman, Lee, S. and Mou-Ling, Dennis 2015. Activities of daily life recognition using process representation modelling to support intention analysis. International Journal of Pervasive Computing and Communications. 11 (3), pp. 347-371. https://doi.org/10.1108/IJPCC-01-2015-0002
Intelligent diagnostic feedback for online multiple-choice questions
Guo, R., Palmer-Brown, D., Lee, S. and Cai, F. F. 2013. Intelligent diagnostic feedback for online multiple-choice questions. Artificial Intelligence Review. 42, p. 369–383. https://doi.org/10.1007/s10462-013-9419-6
Direct state feedback optimal control of a double integrator plant implemented by an artificial neural network
Matieni, Xavier, Dodds, Stephen J. and Lee, S. 2011. Direct state feedback optimal control of a double integrator plant implemented by an artificial neural network. Advances in Computing and Technology. University of East London, London Jan 2011 London University of East London, School of Architecture Computing and Engineering.
Closed-loop control using a backpropagation algorithm: a practicable approach for energy loss minimisation in electrical drives.
Matieni, Xavier, Dodds, Stephen J. and Lee, S. 2010. Closed-loop control using a backpropagation algorithm: a practicable approach for energy loss minimisation in electrical drives. Proceedings of Advances in Computing and Technology, (AC&T) The School of Computing and Technology 5th Annual Conference, University of East London, pp. 72-78
Question response grouping for online diagnostic feedback
Lee, S., Palmer-Brown, Dominic, Draganova, Chrisina, Preston, David and Kretsis, Mike 2009. Question response grouping for online diagnostic feedback. Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 4th Annual Conference University of East London pp. 68-76
Automated updating of road network databases: road segment grouping using snap-drift neural network
Ekpenyong, Frank, Brimicombe, Allan J., Palmer-Brown, Dominic, Li, Yang and Lee, S. 2007. Automated updating of road network databases: road segment grouping using snap-drift neural network. Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 2nd Annual Conference University of East London pp. 160-167
An assessment of neural network algorithms that could aid SME survival
Walcott, Terry H., Palmer-Brown, Dominic, Williams, Godfried, Mouratidis, Haralambos and Lee, S. 2007. An assessment of neural network algorithms that could aid SME survival. Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 2nd Annual Conference University of East London pp. 120-127
Feature discovery using snap-drift neural networks
Lee, S. and Palmer-Brown, Dominic 2007. Feature discovery using snap-drift neural networks. Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 2nd Annual Conference University of East London pp. 61-70
Modal Learning in a Neural Network
Lee, S. and Palmer-Brown, Dominic 2006. Modal Learning in a Neural Network. Proceedings of the AC&T, pp. 42-47
Performance-guided Neural Network for Self-Organising Network Management
Lee, S., Palmer-Brown, Dominic, Tepper, Jonathan and Roadknight, Christopher 2002. Performance-guided Neural Network for Self-Organising Network Management. Proceedings of London Communication Symposium (LCS'2002) University College London, London, UK, 9th – 10th September, pp. 269 - 272
Snap-Drift: Real-time, Performance-guided Learning
Lee, S., Palmer-Brown, Dominic, Tepper, Jonathan and Roadknight, Christopher 2003. Snap-Drift: Real-time, Performance-guided Learning.
Continuous Reinforced Snap-Drift Learning in a Neural Architecture for Proxylet Selection in Active Computer Networks
Palmer-Brown, Dominic and Lee, S. 2005. Continuous Reinforced Snap-Drift Learning in a Neural Architecture for Proxylet Selection in Active Computer Networks. International Journal on Simulation: Systems, Science and Technology. 6 (9), pp. 11-21.
The Analysis of Network Manager’s Behaviour using a Self-Organising Neural Networks
Palmer-Brown, Dominic and Lee, S. 2005. The Analysis of Network Manager’s Behaviour using a Self-Organising Neural Networks. International Journal on Simulation: Systems, Science and Technology. 6 (9), pp. 22-32.
Phonetic Feature Discovery in Speech using Snap-Drift
Lee, S. and Palmer-Brown, Dominic 2006. Phonetic Feature Discovery in Speech using Snap-Drift.
Early SME Market Prediction using USDNN
Walcott, Terry H., Palmer-Brown, Dominic and Lee, S. 2008. Early SME Market Prediction using USDNN. in: Proceedings of the International Conference of Computational Intelligence and Intelligent Systems (ICCIIS'2008) International Association of Engineers.
A Neural Network Approach for Intrusion Detection Systems
Beqiri, Elidon, Lee, S. and Draganova, Chrisina 2010. A Neural Network Approach for Intrusion Detection Systems. 5th Conference in Advances in Computing and Technology (London, United Kingdom, 27th Jan), pp. 209 -217
Diagnostic Feedback by Snap-drift Question Response Grouping
Lee, S., Palmer-Brown, Dominic and Draganova, Chrisina 2008. Diagnostic Feedback by Snap-drift Question Response Grouping. in: Proceedings of 9th WSEAS International Conference on Neural Networks (NN'08) Stevens Point (WI), USA World Scientific and Engineering Academy and Society. pp. 208-214
Modal Learning Neural Networks
Palmer-Brown, Dominic, Lee, S., Draganova, Chrisina and Kang, Miao 2009. Modal Learning Neural Networks.
Snap-Drift Neural Network for Selecting Student Feedback
Palmer-Brown, Dominic, Draganova, Chrisina and Lee, S. 2009. Snap-Drift Neural Network for Selecting Student Feedback. International Joint Conference on Neural Networks, IJCNN 2009. Atlanta, Georgia, USA 14 - 19 Jun 2009 IEEE.