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Artificial Neural Networks – ICANN 2006

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Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Dimensionality Reduction Based on ICA for Regression Problems
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    Chapter 2 A Functional Approach to Variable Selection in Spectrometric Problems
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    Chapter 3 The Bayes-Optimal Feature Extraction Procedure for Pattern Recognition Using Genetic Algorithm
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    Chapter 4 Speeding Up the Wrapper Feature Subset Selection in Regression by Mutual Information Relevance and Redundancy Analysis
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    Chapter 5 Effective Input Variable Selection for Function Approximation
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    Chapter 6 Comparative Investigation on Dimension Reduction and Regression in Three Layer Feed-Forward Neural Network
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    Chapter 7 On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition
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    Chapter 8 Learning Long Term Dependencies with Recurrent Neural Networks
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    Chapter 9 Adaptive On-Line Neural Network Retraining for Real Life Multimodal Emotion Recognition
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    Chapter 10 Time Window Width Influence on Dynamic BPTT(h) Learning Algorithm Performances: Experimental Study
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    Chapter 11 Framework for the Interactive Learning of Artificial Neural Networks
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    Chapter 12 Analytic Equivalence of Bayes a Posteriori Distributions
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    Chapter 13 Neural Network Architecture Selection: Size Depends on Function Complexity
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    Chapter 14 Competitive Repetition-suppression (CoRe) Learning
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    Chapter 15 Real-Time Construction of Neural Networks
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    Chapter 16 MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation
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    Chapter 17 A Variational Formulation for the Multilayer Perceptron
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    Chapter 18 Natural Conjugate Gradient Training of Multilayer Perceptrons
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    Chapter 19 Building Ensembles of Neural Networks with Class-Switching
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    Chapter 20 K-Separability
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    Chapter 21 Lazy Training of Radial Basis Neural Networks
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    Chapter 22 Investigation of Topographical Stability of the Concave and Convex Self-Organizing Map Variant
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    Chapter 23 Alternatives to Parameter Selection for Kernel Methods
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    Chapter 24 Faster Learning with Overlapping Neural Assemblies
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    Chapter 25 Improved Storage Capacity of Hebbian Learning Attractor Neural Network with Bump Formations
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    Chapter 26 Error Entropy Minimization for LSTM Training
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    Chapter 27 Can AdaBoost.M1 Learn Incrementally? A Comparison to Learn  + +  Under Different Combination Rules
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    Chapter 28 Ensemble Learning with Local Diversity
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    Chapter 29 A Machine Learning Approach to Define Weights for Linear Combination of Forecasts
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    Chapter 30 A Game-Theoretic Approach to Weighted Majority Voting for Combining SVM Classifiers
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    Chapter 31 Improving the Expert Networks of a Modular Multi-Net System for Pattern Recognition
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    Chapter 32 Evaluating Users’ Satisfaction in Packet Networks Using Random Neural Networks
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    Chapter 33 Random Neural Networks for the Adaptive Control of Packet Networks
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    Chapter 34 Hardware Implementation of Random Neural Networks with Reinforcement Learning
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    Chapter 35 G-Networks and the Modeling of Adversarial Agents
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    Chapter 36 Development of a Neural Net-Based, Personalized Secure Communication Link
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    Chapter 37 Exact Solutions for Recursive Principal Components Analysis of Sequences and Trees
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    Chapter 38 Active Learning with the Probabilistic RBF Classifier
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    Chapter 39 Merging Echo State and Feedforward Neural Networks for Time Series Forecasting
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    Chapter 40 Language and Cognition Integration Through Modeling Field Theory: Category Formation for Symbol Grounding
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    Chapter 41 A Methodology for Estimating the Product Life Cycle Cost Using a Hybrid GA and ANN Model
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    Chapter 42 Using Self-Organizing Maps to Support Video Navigation
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    Chapter 43 Self-Organizing Neural Networks for Signal Recognition
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    Chapter 44 An Unsupervised Learning Rule for Class Discrimination in a Recurrent Neural Network
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    Chapter 45 On the Variants of the Self-Organizing Map That Are Based on Order Statistics
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    Chapter 46 On the Basis Updating Rule of Adaptive-Subspace Self-Organizing Map (ASSOM)
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    Chapter 47 Composite Algorithm for Adaptive Mesh Construction Based on Self-Organizing Maps
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    Chapter 48 A Parameter in the Learning Rule of SOM That Incorporates Activation Frequency
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    Chapter 49 Nonlinear Projection Using Geodesic Distances and the Neural Gas Network
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    Chapter 50 Contextual Learning in the Neurosolver
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    Chapter 51 A Computational Model for the Effect of Dopamine on Action Selection During Stroop Test
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    Chapter 52 A Neural Network Model of Metaphor Understanding with Dynamic Interaction Based on a Statistical Language Analysis
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    Chapter 53 Strong Systematicity in Sentence Processing by an Echo State Network
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    Chapter 54 Modeling Working Memory and Decision Making Using Generic Neural Microcircuits
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    Chapter 55 A Virtual Machine for Neural Computers
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    Chapter 56 Machine Cognition and the EC Cognitive Systems Projects: Now and in the Future
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    Chapter 57 A Complex Neural Network Model for Memory Functioning in Psychopathology
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    Chapter 58 Modelling Working Memory Through Attentional Mechanisms
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    Chapter 59 A Cognitive Model of Multi-objective Multi-concept Formation
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    Chapter 60 A Basis for Cognitive Machines
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    Chapter 61 Neural Model of Dopaminergic Control of Arm Movements in Parkinson’s Disease Bradykinesia
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    Chapter 62 Occlusion, Attention and Object Representations
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    Chapter 63 A Forward / Inverse Motor Controller for Cognitive Robotics
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    Chapter 64 A Computational Model for Multiple Goals
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    Chapter 65 Detection of a Dynamical System Attractor from Spike Train Analysis
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    Chapter 66 Recurrent Neural Networks Are Universal Approximators
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    Chapter 67 A Discrete Adaptive Stochastic Neural Model for Constrained Optimization
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    Chapter 68 Quantum Perceptron Network
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    Chapter 69 Critical Echo State Networks
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    Chapter 70 Rapid Correspondence Finding in Networks of Cortical Columns
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    Chapter 71 Adaptive Thresholds for Layered Neural Networks with Synaptic Noise
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    Chapter 72 Backbone Structure of Hairy Memory
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    Chapter 73 Dynamics of Citation Networks
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    Chapter 74 Processing of Information in Synchroneously Firing Chains in Networks of Neurons
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    Chapter 75 Phase Precession and Recession with STDP and Anti-STDP
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    Chapter 76 Visual Pathways for Detection of Landmark Points
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    Chapter 77 A Model of Grid Cells Based on a Path Integration Mechanism
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    Chapter 78 Temporal Processing in a Spiking Model of the Visual System
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    Chapter 79 Accelerating Event Based Simulation for Multi-synapse Spiking Neural Networks
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    Chapter 80 A Neurocomputational Model of an Imitation Deficit Following Brain Lesion
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    Chapter 81 Temporal Data Encoding and SequenceLearning with Spiking Neural Networks
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    Chapter 82 Optimal Tuning of Continual Online Exploration in Reinforcement Learning
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    Chapter 83 Vague Neural Network Controller and Its Applications
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    Chapter 84 Parallel Distributed Profit Sharing for PC Cluster
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    Chapter 85 Feature Extraction for Decision-Theoretic Planning in Partially Observable Environments
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    Chapter 86 Reinforcement Learning with Echo State Networks
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    Chapter 87 Reward Function and Initial Values: Better Choices for Accelerated Goal-Directed Reinforcement Learning
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    Chapter 88 Nearly Optimal Exploration-Exploitation Decision Thresholds
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    Chapter 89 Dual Adaptive ANN Controllers Based on Wiener Models for Controlling Stable Nonlinear Systems
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    Chapter 90 Online Stabilization of Chaotic Maps Via Support Vector Machines Based Generalized Predictive Control
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    Chapter 91 Morphological Neural Networks and Vision Based Mobile Robot Navigation
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    Chapter 92 Position Control Based on Static Neural Networks of Anthropomorphic Robotic Fingers
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    Chapter 93 Learning Multiple Models of Non-linear Dynamics for Control Under Varying Contexts
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    Chapter 94 A Study on Optimal Configuration for the Mobile Manipulator: Using Weight Value and Mobility
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    Chapter 95 VSC Perspective for Neurocontroller Tuning
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    Chapter 96 A Neural Network Module with Pretuning for Search and Reproduction of Input-Output Mapping
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    Chapter 97 Physical Mapping of Spiking Neural Networks Models on a Bio-inspired Scalable Architecture
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    Chapter 98 A Time Multiplexing Architecture for Inter-neuron Communications
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    Chapter 99 Neuronal Cell Death and Synaptic Pruning Driven by Spike-Timing Dependent Plasticity
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    Chapter 100 Effects of Analog-VLSI Hardware on the Performance of the LMS Algorithm
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    Chapter 101 A Portable Electronic Nose (E-Nose) System Based on PDA
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    Chapter 102 Optimal Synthesis of Boolean Functions by Threshold Functions
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    Chapter 103 Pareto-optimal Noise and Approximation Properties of RBF Networks
Attention for Chapter 87: Reward Function and Initial Values: Better Choices for Accelerated Goal-Directed Reinforcement Learning
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Citations

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Chapter title
Reward Function and Initial Values: Better Choices for Accelerated Goal-Directed Reinforcement Learning
Chapter number 87
Book title
Artificial Neural Networks – ICANN 2006
Published by
Springer, Berlin, Heidelberg, September 2006
DOI 10.1007/11840817_87
Book ISBNs
978-3-54-038625-4, 978-3-54-038627-8
Authors

Laëtitia Matignon, Guillaume J. Laurent, Nadine Le Fort-Piat

View on publisher site

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 33%
Student > Ph. D. Student 13 27%
Researcher 6 13%
Student > Bachelor 4 8%
Professor > Associate Professor 2 4%
Other 3 6%
Unknown 4 8%
Readers by discipline Count As %
Computer Science 21 44%
Engineering 11 23%
Psychology 1 2%
Agricultural and Biological Sciences 1 2%
Mathematics 1 2%
Other 6 13%
Unknown 7 15%

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