Front matter
3-4
The Complementary Brain (Abstract)
Stephen Grossberg
5-12
Neural Networks for Adaptive Processing of Structured Data
Alessandro Sperduti
13-15
Bad Design and Good Performance: Strategies of the Visual System for Enhanced Scene Analysis
Florentin Wörgötter
19-26
Fast Curvature Matrix-Vector Products
Nicol N. Schraudolph
27-32
Architecture Selection in NLDA Networks
José R. Dorronsoro, Ana M. González and Carlos Santa Cruz
33-40
Neural Learning Invariant to Network Size Changes
Vicente Ruiz de Angulo and Carme Torras
41-48
Boosting Mixture Models for Semi-supervised Learning
Yves Grandvalet, Florence d’Alché-Buc and Christophe Ambroise
49-56
Bagging Can Stabilize without Reducing Variance
Yves Grandvalet
57-64
Symbolic Prosody Modeling by Causal Retro-causal NNs with Variable Context Length
Achim F. Müller and Hans Georg Zimmermann
65-72
Discriminative Dimensionality Reduction Based on Generalized LVQ
Atsushi Sato
73-80
A Computational Intelligence Approach to Optimization with Unknown Objective Functions
Hirotaka Nakayama, Masao Arakawa and Rie Sasaki
81-87
Clustering Gene Expression Data by Mutual Information with Gene Function
Samuel Kaski, Janne Sinkkonen and Janne Nikkilä
87-94
Learning to Learn Using Gradient Descent
Sepp Hochreiter, A. Steven Younger and Peter R. Conwell
95-102
A Variational Approach to Robust Regression
Anita C. Faul and Michael E. Tipping
103-110
Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo
Stephen J. Roberts, Christopher Holmes and Dave Denison
111-118
Behavioral Market Segmentation of Binary Guest Survey Data with Bagged Clustering
Sara Dolničar and Friedrich Leisch
119-126
Direct Estimation of Polynomial Densities in Generalized RBF Networks Using Moments
Evangelos Dermatas
127-134
Generalisation Improvement of Radial Basis Function Networks Based on Qualitative Input Conditioning for Financial Credit Risk Prediction
Xavier Parra, Núria Agell and Xari Rovira
135-140
Approximation of Bayesian Discriminant Function by Neural Networks in Terms of Kullback-Leibler Information
Yoshifusa Ito and Cidambi Srinivasan
141-147
The Bias-Variance Dilemma of the Monte Carlo Method
Zlochin Mark and Yoram Baram
148-155
A Markov Chain Monte Carlo Algorithm for the Quadratic Assignment Problem Based on Replicator Equations
Takehiro Nishiyama, Kazuo Tsuchiya and Katsuyoshi Tsujita
156-163
Mapping Correlation Matrix Memory Applications onto a Beowulf Cluster
Michael Weeks, Jim Austin, Anthony Moulds, Aaron Turner and Zygmunt Ulanowski, et al.
164-169
Accelerating RBF Network Simulation by Using Multimedia Extensions of Modern Microprocessors
Alfred Strey and Martin Bange
170-176
A Game-Theoretic Adaptive Categorization Mechanism for ART-Type Networks
Wai-keung Fung and Yun-hui Liu
177-182
Gaussian Radial Basis Functions and Inner-Product Spaces
Irwin W. Sandberg
183-188
Mixture of Probabilistic Factor Analysis Model and Its Applications
Masahiro Tanaka
189-195
Deferring the Learning for Better Generalization in Radial Basis Neural Networks
José María Valls, Pedro Isasi and Inés María Galván
196-202
Improvement of Cluster Detection and Labeling Neural Network by Introducing Elliptical Basis Function
Christophe Lurette and Stéphane Lecoeuche
203-210
Independent Variable Group Analysis
Krista Lagus, Esa Alhoniemi and Harri Valpola
211-216
Weight Quantization for Multi-layer Perceptrons Using Soft Weight Sharing
Fatih Köksal, Ethem Alpaydyn and Günhan Dündar
217-224
Voting-Merging: An Ensemble Method for Clustering
Evgenia Dimitriadou, Andreas Weingessel and Kurt Hornik
225-230
The Application of Fuzzy ARTMAP in the Detection of Computer Network Attacks
James Cannady and Raymond C. Garcia
231-236
Transductive Learning: Learning Iris Data with Two Labeled Data
Chun Hung Li and Pong Chi Yuen
237-243
Approximation of Time-Varying Functions with Local Regression Models
Achim Lewandowski and Peter Protzel
247-252
Complexity of Learning for Networks of Spiking Neurons with Nonlinear Synaptic Interactions
Michael Schmitt
253-258
Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension
Michael Schmitt
259-264
Generalization Performances of Perceptrons
Gérald Gavin
265-271
Bounds on the Generalization Ability of Bayesian Inference and Gibbs Algorithms
Olivier Teytaud and Hélène Paugam-Moisy
271-276
Learning Curves for Gaussian Processes Models: Fluctuations and Universality
Dörthe Malzahn and Manfred Opper
277-282
Tight Bounds on Rates of Neural-Network Approximation
Věra Kůrková and Marcello Sanguineti
285-291
Scalable Kernel Systems
Volker Tresp and Anton Schwaighofer
292-299
On-Line Learning Methods for Gaussian Processes
Shigeyuki Oba, Masa-aki Sato and Shin Ishii
300-307
Online Approximations for Wind-Field Models
Lehel Csató, Dan Cornford and Manfred Opper
308-313
Fast Training of Support Vector Machines by Extracting Boundary Data
Shigeo Abe and Takuya Inoue
314-321
Multiclass Classification with Pairwise Coupled Neural Networks or Support Vector Machines
Eddy Nicolas Mayoraz
322-330
Incremental Support Vector Machine Learning: A Local Approach
Liva Ralaivola and Florence d’Alché-Buc
331-338
Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers
Koji Tuda, Gunnar Rätsch, Sebastian Mika and Klaus-Robert Müller
339-346
Sparse Kernel Regressors
Volker Roth
347-352
Learning on Graphs in the Game of Go
Thore Graepel, Mike Goutrié, Marco Krüger and Ralf Herbrich
353-360
Nonlinear Feature Extraction Using Generalized Canonical Correlation Analysis
Thomas Melzer, Michael Reiter and Horst Bischof
361-368
Gaussian Process Approach to Stochastic Spiking Neurons with Reset
Ken-ichi Amemori and Shin Ishii
369-375
Kernel Based Image Classification
Olivier Teytaud and David Sarrut
376-383
Gaussian Processes for Model Fusion
Mohammed A. El-Beltagy and W. Andy Wright
384-389
Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines
Tony Van Gestel, Johan A. K. Suykens, Jos De Brabanter, Bart De Moor and Joos Vandewalle
390-398
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Thomas Frontzek, Thomas Navin Lal and Rolf Eckmiller
399-404
Close-Class-Set Discrimination Method for Recognition of Stop_Consonant-Vowel Utterances Using Support Vector Machines
Chellu Chandra Sekhar, Kazuya Takeda and Fumitada Itakura
405-410
Linear Dependency between
ε
and the Input Noise in
ε
-Support Vector Regression
James T. Kwok
411-417
The Bayesian Committee Support Vector Machine
Anton Schwaighofer and Volker Tresp
421-428
Using Directional Curvatures to Visualize Folding Patterns of the GTM Projection Manifolds
Peter Tino, Ian Nabney and Yi Sun
429-435
Self Organizing Map and Sammon Mapping for Asymmetric Proximities
Manuel Martin-Merino and Alberto Muñoz
436-442
Active Learning with Adaptive Grids
Michele Milano, Jürgen Schmidhuber and Petros Koumoutsakos
443-449
Complex Process Visualization through Continuous Feature Maps Using Radial Basis Functions
Ignacio Díaz, Alberto Diez and Abel A. Cuadrado Vega
450-456
A Soft
k
-Segments Algorithm for Principal Curves
Jakob J. Verbeek, Nikos Vlassis and Ben Kröse
457-463
Product Positioning Using Principles from the Self-Organizing Map
Chris Charalambous, George C. Hadjinicola and Eitan Muller
464-469
Combining the Self-Organizing Map and K-Means Clustering for On-Line Classification of Sensor Data
Kristof Van Laerhoven
470-476
Histogram Based Color Reduction through Self-Organized Neural Networks
Antonios Atsalakis, Ioannis Andreadis and Nikos Papamarkos
477-484
Sequential Learning for SOM Associative Memory with Map Reconstruction
Motonobu Hattori, Hiroya Arisumi and Hiroshi Ito
485-491
Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study
Jarkko Venna and Samuel Kaski
492-499
A Topological Hierarchical Clustering: Application to Ocean Color Classification
Méziane Yacoub, Fouad Badran and Sylvie Thiria
500-505
Hierarchical Clustering of Document Archives with the Growing Hierarchical Self-Organizing Map
Michael Dittenbach, Dieter Merkl and Andreas Rauber
509-514
Blind Source Separation of Single Components from Linear Mixtures
Roland Vollgraf, Ingo Schieβl and Klaus Obermayer
515-520
Blind Source Separation Using Principal Component Neural Networks
Konstantinos I. Diamantaras
521-526
Blind Separation of Sources by Differentiating the Output Cumulants and Using Newton’s Method
Rubén Martín-Clemente, José I. Acha and Carlos G. Puntonet
527-534
Mixtures of Independent Component Analysers
Stephen J. Roberts and William D. Penny
535-540
Conditionally Independent Component Extraction for Naive Bayes Inference
Shotaro Akaho
541-546
Fast Score Function Estimation with Application in ICA
Nikos Vlassis
547-553
Health Monitoring with Learning Methods
Alexander Ypma, Co Melissant, Ole Baunbæk-Jensen and Robert P. W. Duin
554-560
Breast Tissue Classification in Mammograms Using ICA Mixture Models
Ioanna Christoyianni, Athanasios Koutras, Evangelos Dermatas and George Kokkinakis
561-567
Neural Network Based Blind Source Separation of Non-linear Mixtures
Athanasios Koutras, Evangelos Dermatas and George Kokkinakis
568-573
Feature Extraction Using ICA
Nojun Kwak, Chong-Ho Choi and Jin Young Choi
577-582
Continuous Speech Recognition with a Robust Connectionist/Markovian Hybrid Model
Edmondo Trentin and Marco Gori
583-592
Faster Convergence and Improved Performance in Least-Squares Training of Neural Networks for Active Sound Cancellation
Martin Bouchard
593-600
Bayesian Independent Component Analysis as Applied to One-Channel Speech Enhancement
Ilyas Potamitis, Nikos Fakotakis and George Kokkinakis
601-608
Massively Parallel Classification of EEG Signals Using Min-Max Modular Neural Networks
Bao-Liang Lu, Jonghan Shin and Michinori Ichikawa
609-616
Single Trial Estimation of Evoked Potentials Using Gaussian Mixture Models with Integrated Noise Component
Arthur Flexer, Herbert Bauer, Claus Lamm and Georg Dorffner
617-624
A Probabilistic Approach to High-Resolution Sleep Analysis
Peter Sykacek, Stephen Roberts, Iead Rezek, Arthur Flexer and Georg Dorffner
625-629
Comparison of Wavelet Thresholding Methods for Denoising ECG Signals
Vladimir Cherkassky and Steven Kilts
630-635
Evoked Potential Signal Estimation Using Gaussian Radial Basis Function Network
G. Sita and A. G. Ramakrishnan
636-641
‘Virtual Keyboard’ Controlled by Spontaneous EEG Activity
Bernhard Obermaier, Gernot Müller and Gert Pfurtscheller
642-649
Clustering of EEG-Segments Using Hierarchical Agglomerative Methods and Self-Organizing Maps
David Sommer and Martin Golz
650-657
Nonlinear Signal Processing for Noise Reduction of Unaveraged Single Channel MEG Data
Wei Lee Woon and David Lowe
661-668
A Discrete Probabilistic Memory Model for Discovering Dependencies in Time
Sepp Hochreiter and Michael C. Mozer
669-676
Applying LSTM to Time Series Predictable through Time-Window Approaches
Felix A. Gers, Douglas Eck and Jürgen Schmidhuber
677-683
Generalized Relevance LVQ for Time Series
Marc Strickert, Thorsten Bojer and Barbara Hammer
684-691
Unsupervised Learning in LSTM Recurrent Neural Networks
Magdalena Klapper-Rybicka, Nicol N. Schraudolph and Jürgen Schmidhuber
692-698
Applying Kernel Based Subspace Classification to a Non-intrusive Monitoring for Household Electric Appliances
Hiroshi Murata and Takashi Onoda
699-705
Neural Networks in Circuit Simulators
Alessio Plebe, A. Marcello Anile and Salvatore Rinaudo
706-711
Neural Networks Ensemble for Cyclosporine Concentration Monitoring
Gustavo Camps, Emilio Soria, José D. Martín, Antonio J. Serrano and Juan J. Ruixo, et al.
712-718
Efficient Hybrid Neural Network for Chaotic Time Series Prediction
Hirotaka Inoue, Yoshinobu Fukunaga and Hiroyuki Narihisa
719-724
Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks
Juan Antonio Pérez-Ortiz, Jorge Calera-Rubio and Mikel L. Forcada
725-730
Prediction Systems Based on FIR BP Neural Networks
Stanislav Kaleta, Daniel Novotný and Peter Sinĉák
731-736
On the Generalization Ability of Recurrent Networks
Barbara Hammer
737-742
Finite-State Reber Automaton and the Recurrent Neural Networks Trained in Supervised and Unsupervised Manner
Michal Cerňanský and Lubica Benuškov
743-748
Estimation of Computational Complexity of Sensor Accuracy Improvement Algorithm Based on Neural Networks
Volodymyr Turchenko, Volodymyr Kochan and Anatoly Sachenko
749-755
Fusion Architectures for the Classification of Time Series
Christian Dietrich, Friedhelm Schwenker and Günther Palm
759-766
The Importance
of Representing
Cognitive Processes in Multi-agent Models
Bruce Edmonds and Scott Moss
767-774
Multi-agent FX-Market Modeling Based on Cognitive Systems
Georg Zimmermann, Ralph Neuneier and Ralph Grothmann
775-781
Speculative Dynamics in a Heterogeneous-Agent Model
Taisei Kaizoji
782-789
Nonlinear Adaptive Beliefs and the Dynamics of Financial Markets: The Role of the Evolutionary Fitness Measure
Andrea Gaunersdorfer and Cars H. Hommes
790-795
Analyzing Purchase Data by a Neural Net Extension of the Multinomial Logit Model
Harald Hruschka, Werner Fettes and Markus Probst
799-805
Using Maximal Recurrence in Linear Threshold Competitive Layer Networks
Heiko Wersing and Helge Ritter
806-814
Exponential Transients in Continuous-Time Symmetric Hopfield Nets
Jiff Sima and Pekka Orponen
814-819
Initial Evolution Results on CAM-Brain Machines (CBMs)
Hugo de Garis, Andrzej Buller, Leo de Penning, Tomasz Chodakowski and Derek Decesare
820-826
Self-Organizing Topology Evolution of Turing Neural Networks
Christof Teuscher and Eduardo Sanchez
827-834
Efficient Pattern Discrimination with Inhibitory WTA Nets
Brijnesh J. Jain and Fritz Wysotzki
835-842
Cooperative Information Control to Coordinate Competition and Cooperation
Ryotaro Kamimura and Taeko Kamimura
843-851
Qualitative Analysis of Continuous Complex-Valued Associative Memories
Yasuaki Kuroe, Naoki Hashimoto and Takehiro Mori
851-856
Self Organized Partitioning of Chaotic Attractors for Control
Nils Goerke, Florian Kintzler and Rolf Eckmiller
857-864
A Generalisable Measure of Self-Organisation and Emergence
W. Andy Wright, Robert E. Smith, Martin Danek and Pillip Greenway
865-873
Market-Based Reinforcement Learning in Partially Observable Worlds
Ivo Kwee, Marcus Hutter and Jürgen Schmidhuber
874-881
Sequential Strategy for Learning Multi-stage Multi-agent Collaborative Games
W. Andy Wright
885-890
Neural Architecture for Mental Imaging of Sequences Based on Optical Flow Predictions
Volker Stephan and Horst-Michael Gross
891-898
Visual Checking of Grasping Positions of a Three-Fingered Robot Hand
Gunther Heidemann and Helge Ritter
899-905
Anticipation-Based Control Architecture for a Mobile Robot
Andrea Heinze and Horst -Michael Gross
906-913
Neural Adaptive Force Control for Compliant Robots
N. Saadia, Y. Amirat, J. Pontnaut and A. Ramdane-Cherif
914-921
A Design of Neural-Net Based Self-Tuning PID Controllers
Michiyo Suzuki, Toru Yamamoto, Kazuo Kawada and Hiroyuki Sogo
922-929
Kinematic Control and Obstacle Avoidance for Redundant Manipulators Using a Recurrent Neural Network
Wai Sum Tang, Cherry Miu Ling Lam and Jun Wang
930-936
Adaptive Neural Control of Nonlinear Systems
Ieroham Baruch, Jose Martin Flores, Federico Thomas and Ruben Garrido
937-942
A Hierarchical Method for Training Embedded Sigmoidal Neural Networks
Jinglu Hu and Kotaro Hirasawa
943-950
Towards Learning Path Planning for Solving Complex Robot Tasks
Thomas Frontzek, Thomas Navin Lal and Rolf Eckmiller
951-956
Hammerstein Model Identification Using Radial Basis Functions Neural Networks
Hussain N. Al-Duwaish and Syed Saad Azhar Ali
957-962
Evolving Neural Behaviour Control for Autonomous Robots
Martin Hülse, Bruno Lara, Frank Pasemann and Ulrich Steinmetz
963-970
Construction by Autonomous Agents in a Simulated Environment
Anand Panangadan and Michael G. Dyer
971-976
A Neural Control Model Using Predictive Adjustment Mechanism of Viscoelastic Property of the Human Arm
Masazumi Katayama
977-984
Multi-joint Arm Trajectory Formation Based on the Minimization Principle Using the Euler-Poisson Equation
Yasuhiro Wada, Yuichi Kaneko, Eri Nakano, Rieko Osu and Mitsuo Kawato
987-992
Neocognitron of a New Version: Handwritten Digit Recognition
Kunihiko Fukushima
993-999
A Comparison of Classifiers for Real-Time Eye Detection
Alex Cozzi, Myron Flickner, Jainchang Mao and Shivakumar Vaithyanathan
1000-1005
Neural Network Analysis of Dynamic Contrast-Enhanced MRI Mammography
Axel Wismüller, Oliver Lange, Dominik R. Dersch, Klaus Hahn and Gerda L. Leinsinger
1006-1012
A New Adaptive Color Quantization Technique
Antonios Atsalakis, Nikos Papamarkos and Charalambos Strouthopoulos
1013-1019
Tunable Oscillatory Network for Visual Image Segmentation
Margarita G. Kuzmina, Eduard A. Manykin and Irina I. Surina
1020-1025
Detecting Shot Transitions for Video Indexing with FAM
Seok-Woo Jang, Gye-Young Kim and Hyung-Il Choi
1026-1033
Finding Faces in Cluttered Still Images with Few Examples
Jan Wieghardt and Hartmut S. Loos
1034-1041
Description of Dynamic Structured Scenes by a SOM/ARSOM Hierarchy
Antonio Chella, Maria Donatella Guarino and Roberto Pirrone
1042-1047
Evaluation of Distance Measures for Partial Image Retrieval Using Self-Organizing Map
Yin Huang, Ponnuthurai N. Suganthan, Shankar M. Krishnan and Xiang Cao
1048-1053
Video Sequence Boundary Detection Using Neural Gas Networks
Xiang Cao and Ponnuthurai N. Suganthan
1054-1059
A Neural-Network-Based Approach to Adaptive Human Computer Interaction
George Votsis, Nikolaos D. Doulamis, Anastasios D. Doulamis, Nicolas Tsapatsoulis and Stefanos D. Kollias
1060-1066
Adaptable Neural Networks for Unsupervised Video Object Segmentation of Stereoscopic Sequences
Anastasios D. Doulamis, Klimis S. Ntalianis, Nikolaos D. Doulamis and Stefanos D. Kollias
1069-1074
A Model of Border-Ownership Coding in Early Vision
Masayuki Kikuchi and Youhei Akashi
1075-1080
Extracting Slow Subspaces from Natural Videos Leads to Complex Cells
Christoph Kayser, Wolfgang Einhäuser, Olaf Dümmer, Peter König and Konrad Körding
1081-1086
Neural Coding of Dynamic Stimuli
Stefan D. Wilke
1087-1094
Resonance of a Stochastic Spiking Neuron Mimicking the Hodgkin-Huxley Model
Ken-ichi Amemori and Shin Ishii
1095-1102
Spike and Burst Synchronization in a Detailed Cortical Network Model with I-F Neurons
Baran Çürüklü and Anders Lansner
1103-1108
Using Depressing Synapses for Phase Locked Auditory Onset Detection
Leslie S. Smith
1109-1114
Controlling Oscillatory Behaviour of a Two Neuron Recurrent Neural Network Using Inputs
Robert Haschke, Jochen J. Steil and Helge Ritter
1115-1120
Temporal Hebbian Learning in Rate-Coded Neural Networks: A Theoretical Approach towards Classical Conditioning
Bernd Porr and Florentin Wörgötter
1121-1128
A Mathematical Analysis of a Correlation Based Model for the Orientation Map Formation
Tadashi Yamazaki
1129-1134
Learning from Chaos: A Model of Dynamical Perception
Emmanuel Daucé
1135-1140
Episodic Memory and Cognitive Map in a Rate Model Network of the Rat Hippocampus
Fanni Misják, Máté Lengyel and Péter Érdi
1141-1146
A Model of Horizontal 360° Object Localization Based on Binaural Hearing and Monocular Vision
Carsten Schauer and Horst-Michael Gross
1147-1152
Self-Organization of Orientation Maps, Lateral Connections, and Dynamic Receptive Fields in the Primary Visual Cortex
Cornelius Weber
1153-1160
Markov Chain Model Approximating the Hodgkin-Huxley Neuron
Yuichi Sakumura, Norio Konno and Kazuyuki Aihara
1163-1170
A Neural Oscillator Model of Auditory Attention
Stuart N. Wrigley and Guy J. Brown
1171-1176
Coupled Neural Maps for the Origins of Vowel Systems
Pierre-yves Oudeyer
1177-1184
Learning for Text Summarization Using Labeled and Unlabeled Sentences
Massih-Reza Amini and Patrick Gallinari
1185-1192
On-Line Error Detection of Annotated Corpus Using Modular Neural Networks
Qing Ma, Bao-Liang Lu, Masaki Murata, Michnori Ichikawa and Hitoshi Isahara
1193-1198
Instance-Based Method to Extract Rules from Neural Networks
DaeEun Kim and Jaeho Lee
1199-1204
A Novel Binary Spell Checker
Victoria J. Hodge and Jim Austin
1205-1210
Neural Nets for Short Movements in Natural Language Processing
Neill Taylor and John Taylor
1211-1216
Using Document Features to Optimize Web Cache
Timo Koskela, Jukka Heikkonen and Kimmo Kaski
1217-1224
Generation of Diversiform Characters Using a Computational Handwriting Model and a Genetic Algorithm
Yasuhiro Wada, Kei Ohkawa and Keiichi Sumita
1225-1232
Information Maximization and Language Acquisition
Ryotaro Kamimura and Taeko Kamimura
1233-1238
A Mirror Neuron System for Syntax Acquisition
Steve Womble and Stefan Wermter
1239-1247
A Network of Relaxation Oscillators that Finds Downbeats in Rhythms
Douglas Eck
1248-1253
Knowledge Incorporation and Rule Extraction in Neural Networks
Minoru Fukumi, Yasue Mitsukura and Norio Akamatsu
Back matter