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
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| 001 | 000000676820 | |
| 005 | 20001101103212 | |
| 008 | 980306s1998 gw a b 001 0 eng | |
| 010 | ▼a 98016268 //r982 | |
| 020 | ▼a 3540643419 (softcover : alk. paper) | |
| 040 | ▼a DLC ▼c DLC ▼d PMC ▼d GZM ▼d C#P ▼d UKM ▼d OHX ▼d 211009 | |
| 049 | 1 | ▼l 121046799 ▼f 과학 |
| 050 | 0 0 | ▼a QA76.87 ▼b .A36 1998 |
| 072 | 7 | ▼a Q ▼2 lcco |
| 082 | 0 0 | ▼a 006.3/2 ▼2 21 |
| 090 | ▼a 006.32 ▼b A221 | |
| 245 | 0 0 | ▼a Adaptive processing of sequences and data structures: ▼b International Summer School on Neural Networks "E.R. Caianiello" Vietri sul Mare, Salerno, Italy, September 6-13 1997, tutorial lectures / ▼c C. Lee Giles, Marco Gori, eds. |
| 260 | ▼a Berlin ; ▼a New York : ▼b Springer , ▼c c1998. | |
| 300 | ▼a xii, 434 p. : ▼b ill. ; ▼c 24 cm. | |
| 490 | 1 | ▼a Lecture notes in computer science ; ▼v 1387. ▼a Lecture notes in artificial intelligence |
| 504 | ▼a Includes bibliographical references and index. | |
| 505 | 0 | ▼a Recurrent neural network architectures : an overview ; Gradient based learning methods / A.C. Tsoi -- Diagrammatic methods for deriving and relating temporal neural network algorithms / E.A. Wan and F. Beaufays -- An introduction to learning structured information / P. Frasconi -- Neural networks for processing data structures / A. Sperduti -- The loading problem : topics in complexity / M. Gori -- Learning dynamic Bayesian networks / Z. Ghahramani -- Probabilistic models of neuronal spike trains / P. Baldi -- Temporal models in blind source separation / L.C. Parra -- Recursive neural networks and automata / M. Maggini -- The neural network pushdown automaton : architecture, dynamics and training / G.Z. Sun, C.L. Giles and H.H. Chen -- Neural dynamics with stochasticity / H.T. Siegelmann -- Parsing the stream of time : the value of event-based segmentation in a complex real-world control problem / M.C. Mozer and D. Miller -- Hybrid HMM/ANN systems for speech recognition : overview and new research directions / H. Bourlard and N. Morgan -- Predictive models for sequence modelling, application to speech and character recognition / P. Gallinari. |
| 650 | 0 | ▼a Neural networks (Computer science) |
| 650 | 0 | ▼a Data structures (Computer science) |
| 650 | 0 | ▼a Parallel processing (Electronic computers) |
| 700 | 1 | ▼a Giles, C. Lee. |
| 700 | 1 | ▼a Gori, Marco. |
| 711 | 2 | ▼a International Summer School on Neural Networks ▼d (1997 : ▼c Salerno, Italy) |
| 830 | 0 | ▼a Lecture notes in computer science ; ▼v 1387. |
| 830 | 0 | ▼a Lecture notes in computer science. ▼p Lecture notes in artificial intelligence. |
Holdings Information
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| No. 1 | Location Science & Engineering Library/Sci-Info(Stacks2)/ | Call Number 006.32 A221 | Accession No. 121046799 | Availability Available | Due Date | Make a Reservation | Service |
Contents information
Book Introduction
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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Table of Contents
Recurrent neural network architectures: An overview.- Gradient based learning methods.- Diagrammatic methods for deriving and relating temporal neural network algorithms.- An introduction to learning structured information.- Neural networks for processing data structures.- The loading problem: Topics in complexity.- Learning dynamic Bayesian networks.- Probabilistic models of neuronal spike trains.- Temporal models in blind source separation.- Recursive neural networks and automata.- The neural network pushdown automaton: Architecture, dynamics and training.- Neural dynamics with stochasticity.- Parsing the stream of time: The value of event-based segmentation in a complex real-world control problem.- Hybrid HMM/ANN systems for speech recognition: Overview and new research directions.- Predictive models for sequence modelling, application to speech and character recognition.
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