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Adaptive Processing of Sequences and Data Structures

International Summer School on Neural Networks, "E.R. Caianiello", Vietri sul Mare, Salerno, Italy, September 6-13, 1997, Tutorial Lectures

  • Textbook
  • © 1998

Overview

Editors:
  1. C. Lee Giles
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  2. Marco Gori
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  • The book originates from a summer school held in September 1997 and is thus ideally suited for advanced courses on adaptive information processing and advanced learning techniques or for self-instruction.
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1387)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: NN 1997.

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Table of contents (15 chapters)

  1. Front Matter

    Download chapter PDF

  2. Recurrent neural network architectures: An overview

    • Ah Chung Tsoi
    Pages 1-26

  3. Gradient based learning methods

    • Ah Chung Tsoi, Ah Chung Tsoi
    Pages 27-62

  4. Diagrammatic methods for deriving and relating temporal neural network algorithms

    • Eric A. Wan, Françoise Beaufays
    Pages 63-98

  5. An introduction to learning structured information

    • Paolo Frasconi
    Pages 99-120

  6. Neural networks for processing data structures

    • Alessandro Sperduti
    Pages 121-144

  7. The loading problem: Topics in complexity

    • Marco Gori
    Pages 145-167

  8. Learning dynamic Bayesian networks

    • Zoubin Ghahramani
    Pages 168-197

  9. Probabilistic models of neuronal spike trains

    • Pierre Baldi
    Pages 198-228

  10. Temporal models in blind source separation

    • Lucas C. Parra
    Pages 229-247

  11. Recursive neural networks and automata

    • Marco Maggini
    Pages 248-295

  12. The neural network pushdown automaton: Architecture, dynamics and training

    • G. Z. Sun, C. L. Giles, H. H. Chen
    Pages 296-345

  13. Neural dynamics with stochasticity

    • Hava T. Siegelmann
    Pages 346-369

  14. Parsing the stream of time: The value of event-based segmentation in a complex real-world control problem

    • Michael C. Mozer, Debra Miller
    Pages 370-388

  15. Hybrid HMM/ANN systems for speech recognition: Overview and new research directions

    • Hervé Bourlard, Nelson Morgan
    Pages 389-417

  16. Predictive models for sequence modelling, application to speech and character recognition

    • P. Gallinari
    Pages 418-434
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Keywords

About this book

This book is devoted to adaptive processing of structured information similar to flexible and intelligent information processing by humans - in contrast to merely sequential processing of predominantly symbolic information within a deterministic framework. Adaptive information processing allows for a mixture of sequential and parallel processing of symbolic as well as subsymbolic information within deterministic and probabilistic frameworks.
The book originates from a summer school held in September 1997 and thus is ideally suited for advanced courses on adaptive information processing and advanced learning techniques or for self-instruction. Research and design professionals active in the area of neural information processing will find it a valuable state-of-the-art survey.

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