18. ICANN 2008: Prague, Czech Republic

Mathematical Theory of Neurocomputing

• Shotaro Akaho:
  Dimension Reduction for Mixtures of Exponential Families. 1-10
  
• Bartlomiej Beliczynski, Bernardete Ribeiro:
  Several Enhancements to Hermite-Based Approximation of One-Variable Functions. 11-20
  
• Yoshifusa Ito, Cidambi Srinivasan, Hiroyuki Izumi:
  Multi-category Bayesian Decision by Neural Networks. 21-30
  
• Paul C. Kainen, Vera Kurková:
  Estimates of Network Complexity and Integral Representations. 31-40
  
• Sascha Klement, Amir Madany Mamlouk, Thomas Martinetz:
  Reliability of Cross-Validation for SVMs in High-Dimensional, Low Sample Size Scenarios. 41-50
  
• Yu Nishiyama, Sumio Watanabe:
  Generalization of Concave and Convex Decomposition in Kikuchi Free Energy. 51-60
  
• Yutaka Shimada, Takayuki Kimura, Tohru Ikeguchi:
  Analysis of Chaotic Dynamics Using Measures of the Complex Network Theory. 61-70
  
• Martin Schüle, Thomas Ott, Ruedi Stoop:
  Global Dynamics of Finite Cellular Automata. 71-78
  

Learning Algorithms

• Mohamed Farouk Abdel Hady, Friedhelm Schwenker, Günther Palm:
  Semi-supervised Learning of Tree-Structured RBF Networks Using Co-training. 79-88
  
• Jiaoyan Ai, Brian V. Funt, Lilong Shi:
  A New Type of ART2 Architecture and Application to Color Image Segmentation. 89-98
  
• Bruno Apolloni, Simone Bassis, Andrea Brega:
  BICA: A Boolean Indepenedent Component Analysis Approach. 99-108
  
• Débora C. Corrêa, Alexandre L. M. Levada, José Hiroki Saito:
  Improving the Learning Speed in 2-Layered LSTM Network by Estimating the Configuration of Hidden Units and Optimizing Weights Initialization. 109-118
  
• Wei-Chen Cheng, Cheng-Yuan Liou:
  Manifold Construction Using the Multilayer Perceptron. 119-127
  
• Cezary Dendek, Jacek Mandziuk:
  Improving Performance of a Binary Classifier by Training Set Selection. 128-135
  
• Yoshitatsu Matsuda, Kazunori Yamaguchi:
  An Overcomplete ICA Algorithm by InfoMax and InfoMin. 136-144
  
• Yoan Miche, Antti Sorjamaa, Amaury Lendasse:
  OP-ELM: Theory, Experiments and a Toolbox. 145-154
  
• Ezequiel López-Rubio, Juan Miguel Ortiz-de-Lazcano-Lobato, Domingo López-Rodríguez, María del Carmen Vargas-González:
  Robust Nonparametric Probability Density Estimation by Soft Clustering. 155-164
  
• Yasunori Nishimori, Shotaro Akaho, Mark D. Plumbley:
  Natural Conjugate Gradient on Complex Flag Manifolds for Complex Independent Subspace Analysis. 165-174
  
• Marco Signoretto, Kristiaan Pelckmans, Johan A. K. Suykens:
  Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation. 175-184
  
• Luís M. Silva, Mark Embrechts, Jorge M. Santos, Joaquim Marques de Sá:
  The Influence of the Risk Functional in Data Classification with MLPs. 185-194
  
• Stelios Timotheou:
  Nonnegative Least Squares Learning for the Random Neural Network. 195-204
  

Kernel Methods, Statistical Learning, and Ensemble Techniques

• Daniel Hernández-Lobato:
  Sparse Bayes Machines for Binary Classification. 205-214
  
• Katerina Hlavácková-Schindler:
  Tikhonov Regularization Parameter in Reproducing Kernel Hilbert Spaces with Respect to the Sensitivity of the Solution. 215-224
  
• Peter Lacko, Vladimir Kvasnicka:
  Mixture of Expert Used to Learn Game Play. 225-234
  
• Daniel Oberhoff, Marina Kolesnik:
  Unsupervised Bayesian Network Learning for Object Recognition in Image Sequences. 235-244
  
• Laura Emmanuella A. Santana, Anne M. P. Canuto, João Carlos Xavier Jr.:
  Using Feature Distribution Methods in Ensemble Systems Combined by Fusion and Selection-Based Methods. 245-254
  
• Ke Sun, Lei Xu:
  Bayesian Ying-Yang Learning on Orthogonal Binary Factor Analysis. 255-264
  
• Shikui Tu, Lei Shi, Lei Xu:
  A Comparative Study on Data Smoothing Regularization for Local Factor Analysis. 265-274
  
• Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
  Adding Diversity in Ensembles of Neural Networks by Reordering the Training Set. 275-284
  
• Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
  New Results on Combination Methods for Boosting Ensembles. 285-294
  

Support Vector Machines

• Shigeo Abe:
  Batch Support Vector Training Based on Exact Incremental Training. 295-304
  
• Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti:
  A Kernel Method for the Optimization of the Margin Distribution. 305-314
  
• Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro:
  A 4-Vector MDM Algorithm for Support Vector Training. 315-324
  
• Honorius Gâlmeanu, Razvan Andonie:
  Implementation Issues of an Incremental and Decremental SVM. 325-335
  
• Khaled Boukharouba, Stéphane Lecoeuche:
  Online Clustering of Non-stationary Data Using Incremental and Decremental SVM. 336-345
  
• Tomasz Maszczyk, Wlodzislaw Duch:
  Support Vector Machines for Visualization and Dimensionality Reduction. 346-356
  

Reinforcement Learning

• Marek Grzes, Daniel Kudenko:
  Multigrid Reinforcement Learning with Reward Shaping. 357-366
  
• Yu Hiei, Takeshi Mori, Shin Ishii:
  Self-organized Reinforcement Learning Based on Policy Gradient in Nonstationary Environments. 367-376
  
• Makoto Otsuka, Junichiro Yoshimoto, Kenji Doya:
  Robust Population Coding in Free-Energy-Based Reinforcement Learning. 377-386
  
• Frank Sehnke, Christian Osendorfer, Thomas Rückstieß, Alex Graves, Jan Peters, Jürgen Schmidhuber:
  Policy Gradients with Parameter-Based Exploration for Control. 387-396
  
• Yuki Taniguchi, Takeshi Mori, Shin Ishii:
  A Continuous Internal-State Controller for Partially Observable Markov Decision Processes. 397-406
  
• Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber:
  Episodic Reinforcement Learning by Logistic Reward-Weighted Regression. 407-416
  
• Jernej Zupanc:
  Error-Entropy Minimization for Dynamical Systems Modeling. 417-425
  

Evolutionary Computing

• Zdenek Buk, Miroslav Snorek:
  Hybrid Evolution of Heterogeneous Neural Networks. 426-434
  
• Oleg Kovárík, Miroslav Skrbek:
  Ant Colony Optimization with Castes. 435-442
  
• David Lahoz, Pedro Mateo:
  Neural Network Ensembles for Classification Problems Using Multiobjective Genetic Algorithms. 443-451
  
• Daniel Novák, Ales Pilný, Pavel Kordík, Stefan Holiga, Petr Posík, R. Cerný, Richard Brzezny:
  Analysis of Vestibular-Ocular Reflex by Evolutionary Framework. 452-461
  
• Tomás Siegl, Pavel Kordík, Miroslav Snorek, Pavel Calda:
  Fetal Weight Prediction Models: Standard Techniques or Computational Intelligence Methods?. 462-471
  
• Hong Zhang, Masumi Ishikawa:
  Evolutionary Canonical Particle Swarm Optimizer - A Proposal of Meta-optimization in Model Selection. 472-481
  

Hybrid Systems

• Marcin Blachnik, Wlodzislaw Duch:
  Building Localized Basis Function Networks Using Context Dependent Clustering. 482-491
  
• Alexandros Chortaras, Giorgos B. Stamou, Andreas Stafylopatis, Stefanos D. Kollias:
  Adaptation of Connectionist Weighted Fuzzy Logic Programs with Kripke-Kleene Semantics. 492-502
  
• Boguslaw Cyganek:
  Neuro-fuzzy System for Road Signs Recognition. 503-512
  
• Arfan Ghani, T. Martin McGinnity, Liam P. Maguire, Jim Harkin:
  Neuro-inspired Speech Recognition with Recurrent Spiking Neurons. 513-522
  
• Silvio B. Guerra, Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir:
  Predicting the Performance of Learning Algorithms Using Support Vector Machines as Meta-regressors. 523-532
  
• Petr Hájek, Vladimír Olej:
  Municipal Creditworthiness Modelling by Kohonen's Self-Organizing Feature Maps and Fuzzy Logic Neural Networks. 533-542
  
• Roman Neruda, Václav Snásel, Jan Platos, Pavel Krömer, Dusan Húsek, Alexander A. Frolov:
  Implementing Boolean Matrix Factorization. 543-552
  
• Vladimir Kryzhanovsky, Boris Kryzhanovsky, Anatoly B. Fonarev:
  Application of Potts-Model Perceptron for Binary Patterns Identification. 553-561
  
• Araken de Medeiros Santos, Anne Magaly de Paula Canuto:
  Using ARTMAP-Based Ensemble Systems Designed by Three Variants of Boosting. 562-571
  

Self-organization

• Banchar Arnonkijpanich, Barbara Hammer, Alexander Hasenfuss, Chidchanok Lursinsap:
  Matrix Learning for Topographic Neural Maps. 572-582
  
• Antonino Fiannaca, Giuseppe Di Fatta, Salvatore Gaglio, Riccardo Rizzo, Alfonso Urso:
  Clustering Quality and Topology Preservation in Fast Learning SOMs. 583-592
  
• Claudius Gläser, Frank Joublin, Christian Goerick:
  Enhancing Topology Preservation during Neural Field Development Via Wiring Length Minimization. 593-602
  
• Timo Honkela, Sami Virpioja, Jaakko J. Väyrynen:
  Adaptive Translation: Finding Interlingual Mappings Using Self-Organizing Maps. 603-612
  
• Hirotaka Inoue:
  Self-Organizing Neural Grove: Efficient Multiple Classifier System with Pruned Self-Generating Neural Trees. 613-622
  
• Hideyuki Kato, Tohru Ikeguchi:
  Self-organized Complex Neural Networks through Nonlinear Temporally Asymmetric Hebbian Plasticity. 623-631
  
• Jan Koutník, Miroslav Snorek:
  Temporal Hebbian Self-Organizing Map for Sequences. 632-641
  
• Iván Machón González, Hilario López García:
  FLSOM with Different Rates for Classification in Imbalanced Datasets. 642-651
  
• Lucia Maddalena, Alfredo Petrosino:
  A Self-organizing Neural System for Background and Foreground Modeling. 652-661
  
• Víctor Mireles, Antonio Neme:
  Analyzing the Behavior of the SOM through Wavelet Decomposition of Time Series Generated during Its Execution. 662-670
  
• Antonio Neme, Elizabeth Chavez, Alejandra Cervera, Víctor Mireles:
  Decreasing Neighborhood Revisited in Self-Organizing Maps. 671-679
  
• Esteban J. Palomo, Enrique Domínguez, Rafael Marcos Luque, José Muñoz:
  A New GHSOM Model Applied to Network Security. 680-689
  
• Matús Uzák, Rudolf Jaksa, Peter Sincak:
  Reduction of Visual Information in Neural Network Learning Visualization. 690-699
  

Control and Robotics

• Péter Gasztonyi, István Harmati:
  Heuristiscs-Based High-Level Strategy for Multi-agent Systems. 700-709
  
• Sven Hellbach, Sören Strauss, Julian Eggert, Edgar Körner, Horst-Michael Gross:
  Echo State Networks for Online Prediction of Movement Data - Comparing Investigations. 710-719
  
• Stanislav Slusny, Roman Neruda, Petra Vidnerová:
  Comparison of RBF Network Learning and Reinforcement Learning on the Maze Exploration Problem. 720-729
  
• Johane Takeuchi, Osamu Shouno, Hiroshi Tsujino:
  Modular Neural Networks for Model-Free Behavioral Learning. 730-739
  
• Cornelius Weber, Jochen Triesch:
  From Exploration to Planning. 740-749
  

Signal and Time Series Processing

• Theologos Athanaselis, Stelios Bakamidis, Konstantinos Mamouras, Ioannis Dologlou:
  Sentence-Level Evaluation Using Co-occurences of N-Grams. 750-758
  
• Pau Bofill:
  Identifying Single Source Data for Mixing Matrix Estimation in Instantaneous Blind Source Separation. 759-767
  
• Miroslav Cepek, Miroslav Snorek, Václav Chudácek:
  ECG Signal Classification Using GAME Neural Network and Its Comparison to Other Classifiers. 768-777
  
• Michal Cernanský, Peter Tiño:
  Predictive Modeling with Echo State Networks. 778-787
  
• Kai Labusch, Erhardt Barth, Thomas Martinetz:
  Sparse Coding Neural Gas for the Separation of Noisy Overcomplete Sources. 788-797
  
• Rashidi Khazaee Parviz, Nasser Mozayani, Mohammad-Reza Jahed Motlagh:
  Mutual Information Based Input Variable Selection Algorithm and Wavelet Neural Network for Time Series Prediction. 798-807
  
• Francis Wyffels, Benjamin Schrauwen, Dirk Stroobandt:
  Stable Output Feedback in Reservoir Computing Using Ridge Regression. 808-817
  

Image Processing

• Mohamed Berkane, Patrick Clarysse, Isabelle E. Magnin:
  Spatio-temporal Summarizing Method of Periodic Image Sequences with Kohonen Maps. 818-826
  
• Marcin Blachnik, Jorma Laaksonen:
  Image Classification by Histogram Features Created with Learning Vector Quantization. 827-836
  
• Nizar Bouguila, Walid ElGuebaly:
  A Statistical Model for Histogram Refinement. 837-846
  
• Vasileios Chasanis, Aristidis Likas, Nikolas P. Galatsanos:
  Efficient Video Shot Summarization Using an Enhanced Spectral Clustering Approach. 847-856
  
• David Elizondo, Shang-Ming Zhou, Charalambos Chrysostomou:
  Surface Reconstruction Techniques Using Neural Networks to Recover Noisy 3D Scenes. 857-866
  
• Benedikt Kaiser, Gunther Heidemann:
  A Spatio-temporal Extension of the SUSAN-Filter. 867-876
  
• Rafael Marcos Luque Baena, Enrique Domínguez, Domingo López-Rodríguez, Esteban J. Palomo:
  A Neighborhood-Based Competitive Network for Video Segmentation and Object Detection. 877-886
  
• Marco Mora Cofré, Ruben Valenzuela, Girma Berhe:
  A Hierarchic Method for Footprint Segmentation Based on SOM. 887-896
  
• Judith Redi, Paolo Gastaldo, Rodolfo Zunino, Ingrid Heynderickx:
  Co-occurrence Matrixes for the Quality Assessment of Coded Images. 897-906
  
• Nikos Simou, Thanos Athanasiadis, Stefanos D. Kollias, Giorgos B. Stamou, Andreas Stafylopatis:
  Semantic Adaptation of Neural Network Classifiers in Image Segmentation. 907-916
  
• Marina Velikova, Hennie Daniels, Maurice Samulski:
  Partially Monotone Networks Applied to Breast Cancer Detection on Mammograms. 917-926
  

Image Processing - Recognition Systems

• Stylianos Asteriadis, Kostas Karpouzis, Stefanos D. Kollias:
  A Neuro-fuzzy Approach to User Attention Recognition. 927-936
  
• Thomas Bangert:
  TriangleVision: A Toy Visual System. 937-950
  
• Alberto Ferreira de Souza, Claudine Badue, Felipe Pedroni, Elias Oliveira, Stiven Schwanz Dias, Hallysson Oliveira, Sotério Ferreira de Souza:
  Face Recognition with VG-RAM Weightless Neural Networks. 951-960
  
• Mathias Franzius, Niko Wilbert, Laurenz Wiskott:
  Invariant Object Recognition with Slow Feature Analysis. 961-970
  
• Vinod Nair, Josh Susskind, Geoffrey E. Hinton:
  Analysis-by-Synthesis by Learning to Invert Generative Black Boxes. 971-981
  
• Pedro L. Sánchez Orellana, Claudio Castellanos Sánchez:
  A Bio-inspired Connectionist Architecture for Visual Classification of Moving Objects. 982-990
  
• Yasuomi D. Sato, Jenia Jitsev, Christoph von der Malsburg:
  A Visual Object Recognition System Invariant to Scale and Rotation. 991-1000
  
• Aruna Shenoy, Tim M. Gale, Neil Davey, Bruce Christianson, Ray J. Frank:
  Recognizing Facial Expressions: A Comparison of Computational Approaches. 1001-1010
  
• Daniel Weiler, Volker Willert, Julian Eggert:
  A Probabilistic Prediction Method for Object Contour Tracking. 1011-1020