Skip to main content
SpringerLink
Log in

VC-Dimension of a Context-Dependent Perceptron

  • Conference paper
  • First Online:
Modeling and Using Context (CONTEXT 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2116))

Abstract

In the paper, we present the model of a context-dependent neural net - a net which may change the way it works according to the external conditions. The information about the environmental conditions is fed to the net through the context inputs, which are used to calculate the net’s weights, and as a consequence modify the way the net reacts to the traditional inputs.

We discuss the Vapnik-Chervonenkis dimension of such a neuron and show that the separating power of a context-dependent neuron and multilayer net grows with the number of adjustable parameters. We present the difference in the way traditional and context-dependent nets work and compare the input space transformations both of them are able to perform. We also show that context-dependent nets learn faster than traditional ones with the same VC-dimension.

Paper supported by Wrocław University of Technology grant no. 332291

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Turney P.: The Identification of Context-Sensitive Features: A Formal Definition of Context for Concept Learning, Proc. of 13th International Conference on Machine Learning (ICML96), Workshop on Learning in Context-Sensitive Domains, Bari, Italy, 1996

    Google Scholar 

  2. Turney P.: The Management of Context-Sensitive Features: A Review of Strategies, Proc. of ICML96, Bari, Italy, 1996

    Google Scholar 

  3. Turney P.: Exploiting context when learning to classify, Proc. of ICML93, Springer-Verlag

    Google Scholar 

  4. Harries M., Sammut C., Horn K.: Extracting hidden contexts, Machine Learning 32

    Google Scholar 

  5. Yeung D.T., Bekey G.A.: Using a context-sensitive learning to robot arm control, Proc. IEEE Int. Conf. on Robotics and Automation, pp 1441–1447, 1989

    Google Scholar 

  6. Anthony M., Bartlett P.L.: Neural Network Learning: Theoretical Foundations, Cambridge University Press, 1999, Cambridge

    Google Scholar 

  7. Rafajłowicz E.: Context Dependent Neural Nets-Problem Statement and Examples (Part 1), Learning (Part 2), Proc. of 3rd Conference Neural Networks and Their Applications, Zakopane, Poland, 1999

    Google Scholar 

  8. Ciskowski P., Rafajłowicz E.: Context Dependent Neural Nets-Structures and Learning, to be published in IEEE Trans. on Neural Networks

    Google Scholar 

  9. Watrous R.L., Towell G.: A Patient-Adaptive Neural Network ECG Patient Monitoring Algorithm. In Proc. Computers in Cardiology 1995, Vienna, Austria.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Engineering Cybernetics, Wrocław University of Technology, Wybrzeyze Wyspiańskiego 27, 50 370, Wrocłlaw, Poland

    Piotr Ciskowski

Authors
  1. Piotr Ciskowski
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Bilkent University, Bilkent, Ankara, 06533, Turkey

    Varol Akman

  2. Department of Computer and Management Sciences, University of Trento, 38100, Trento, Italy

    Paolo Bouquet

  3. Philosophy Department, University of Michigan, 2251 Angell Hall, Ann Arbor, MI, 48109-1003, USA

    Richmond Thomason

  4. Philosophy Department, University of Dundee, Dundee, DD1 4HN, Scotland, UK

    Roger Young

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ciskowski, P. (2001). VC-Dimension of a Context-Dependent Perceptron. In: Akman, V., Bouquet, P., Thomason, R., Young, R. (eds) Modeling and Using Context. CONTEXT 2001. Lecture Notes in Computer Science(), vol 2116. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44607-9_36

Download citation

  • DOI: https://doi.org/10.1007/3-540-44607-9_36

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42379-9

  • Online ISBN: 978-3-540-44607-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation