19. ICANN 2009: Limassol, Cyprus

Learning Algorithms

• Alberto Guillén, Antti Sorjamaa, Ginés Rubio, Amaury Lendasse, Ignacio Rojas:
  Mutual Information Based Initialization of Forward-Backward Search for Feature Selection in Regression Problems. 1-9
  
• Hong Zeng, Yiu-ming Cheung:
  Kernel Learning for Local Learning Based Clustering. 10-19
  
• Zhirong Yang, Erkki Oja:
  Projective Nonnegative Matrix Factorization with α-Divergence. 20-29
  
• Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir:
  Active Generation of Training Examples in Meta-Regression. 30-39
  
• Edmondo Trentin, Leonardo Rigutini:
  A Maximum-Likelihood Connectionist Model for Unsupervised Learning over Graphical Domains. 40-49
  
• Dimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos:
  Local Feature Selection for the Relevance Vector Machine Using Adaptive Kernel Learning. 50-59
  
• Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel:
  MINLIP: Efficient Learning of Transformation Models. 60-69
  
• Alexander Hans, Steffen Udluft:
  Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data. 70-79
  
• Krzysztof Patan, Maciej Patan:
  Optimal Training Sequences for Locally Recurrent Neural Networks. 80-89
  
• Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez:
  Statistical Instance-Based Ensemble Pruning for Multi-class Problems. 90-99
  
• Kris De Brabanter, Kristiaan Pelckmans, Jos De Brabanter, Michiel Debruyne, Johan A. K. Suykens, Mia Hubert, Bart De Moor:
  Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes. 100-110
  
• Kristina Davoian, Wolfram-Manfred Lippe:
  Mixing Different Search Biases in Evolutionary Learning Algorithms. 111-120
  
• Mohamed Farouk Abdel Hady, Friedhelm Schwenker, Günther Palm:
  Semi-supervised Learning for Regression with Co-training by Committee. 121-130
  
• Rodrigo G. F. Soares, Teresa Bernarda Ludermir, Francisco de A. T. de Carvalho:
  An Analysis of Meta-learning Techniques for Ranking Clustering Algorithms Applied to Artificial Data. 131-140
  
• Cezary Dendek, Jacek Mandziuk:
  Probability-Based Distance Function for Distance-Based Classifiers. 141-150
  
• Marek Grochowski, Wlodzislaw Duch:
  Constrained Learning Vector Quantization or Relaxed k-Separability. 151-160
  
• Leonid B. Litinskii:
  Minimization of Quadratic Binary Functional with Additive Connection Matrix. 161-170
  
• Kazuyuki Hara, Yoichi Nakayama, Seiji Miyoshi, Masato Okada:
  Mutual Learning with Many Linear Perceptrons: On-Line Learning Theory. 171-180
  

Computational Neuroscience

• Karim El-Laithy, Martin Bogdan:
  Synchrony State Generation in Artificial Neural Networks with Stochastic Synapses. 181-190
  
• Florian Hauser, David Bouchain, Günther Palm:
  Coexistence of Cell Assemblies and STDP. 191-197
  
• Kevin Gurney, Amir Hussain, Jonathan M. Chambers, Rudwan Abdullah:
  Controlled and Automatic Processing in Animals and Machines with Application to Autonomous Vehicle Control. 198-207
  
• Jindong Liu, David Perez-Gonzalez, Adrian Rees, Harry R. Erwin, Stefan Wermter:
  Multiple Sound Source Localisation in Reverberant Environments Inspired by the Auditory Midbrain. 208-217
  
• Emmanuel Daucé:
  A Model of Neuronal Specialization Using Hebbian Policy-Gradient with "Slow" Noise. 218-228
  
• Vassilis Cutsuridis, Stuart Cobb, Bruce P. Graham:
  How Bursts Shape the STDP Curve in the Presence/Absence of GABAergic Inhibition. 229-238
  
• Prashant Joshi, Jochen Triesch:
  Optimizing Generic Neural Microcircuits through Reward Modulated STDP. 239-248
  
• Takashi Nakano, Junichiro Yoshimoto, Jeff Wickens, Kenji Doya:
  Calcium Responses Model in Striatum Dependent on Timed Input Sources. 249-258
  
• Rodolfo V. García, Fernando Rojas, Jesús González, Belén San Román, Olga Valenzuela, Alberto Prieto, Luis Velázquez, Roberto Rodríguez:
  Independent Component Analysis Aided Diagnosis of Cuban Spino Cerebellar Ataxia 2. 259-266
  
• Ansgar Koene, Tony J. Prescott:
  Hippocampus, Amygdala and Basal Ganglia Based Navigation Control. 267-276
  
• Vladyslav V. Shaposhnyk, Pierre Dutoit, Victor Contreras-Lámus, Stephen Perrig, Alessandro E. P. Villa:
  A Framework for Simulation and Analysis of Dynamically Organized Distributed Neural Networks. 277-286
  
• Haixian Zhang, Jiali Yu, Zhang Yi:
  Continuous Attractors of Lotka-Volterra Recurrent Neural Networks. 287-295
  
• Kiran V. Byadarhaly, Mithun Perdoor, Suresh Vasa, Emmanuel Fernandez, Ali A. Minai:
  Learning Complex Population-Coded Sequences. 296-305
  
• Hideyuki Kato, Tohru Ikeguchi, Kazuyuki Aihara:
  Structural Analysis on STDP Neural Networks Using Complex Network Theory. 306-314
  
• Márton Albert Hajnal:
  Time Coding of Input Strength Is Intrinsic to Synapses with Short Term Plasticity. 315-324
  
• Andrea Guazzini, Pietro Liò, Andrea Passarella, Marco Conti:
  Information Processing and Timing Mechanisms in Vision. 325-334
  
• German D. Valderrama-Gonzalez, T. Martin McGinnity, Liam P. Maguire, Qingxiang Wu:
  Review of Neuron Types in the Retina: Information Models for Neuroengineering. 335-344
  
• Wichian Sittiprapaporn, Jun Soo Kwon:
  Brain Electric Microstate and Perception of Simultaneously Audiovisual Presentation. 345-355
  
• José R. A. Torreão, João L. Fernandes, Silvia M. C. Victer:
  A Model for Neuronal Signal Representation by Stimulus-Dependent Receptive Fields. 356-362
  

Hardware Implementations and Embedded Systems

• Emil Raschman, Daniela Durackova:
  Area Chip Consumption by a Novel Digital CNN Architecture for Pattern Recognition. 363-372
  
• Alexander Guzhva, Sergey Dolenko, Igor Persiantsev:
  Multifold Acceleration of Neural Network Computations Using GPU. 373-380
  
• Michal Cernanský:
  Training Recurrent Neural Network Using Multistream Extended Kalman Filter on Multicore Processor and Cuda Enabled Graphic Processor Unit. 381-390
  
• Norihiro Takahashi, Tadashi Shibata:
  A Non-subtraction Configuration of Self-similitude Architecture for Multiple-Resolution Edge-Filtering CMOS Image Sensor. 391-400
  
• Chih-Cheng Lu, H. Chen:
  Current-Mode Computation with Noise in a Scalable and Programmable Probabilistic Neural VLSI System. 401-409
  
• Chih-Cheng Lu, H. Chen:
  Minimising Contrastive Divergence with Dynamic Current Mirrors. 410-420
  
• José Luis Rosselló, Ivan de Paúl, Vincent Canals, Antoni Morro:
  Spiking Neural Network Self-configuration for Temporal Pattern Recognition Analysis. 421-428
  
• Gonzalo Carvajal, Waldo Valenzuela, Miguel Figueroa:
  Image Recognition in Analog VLSI with On-Chip Learning. 429-438
  
• Lambert Spaanenburg, Mona Akbarniai Tehrani, Richard P. Kleihorst, Peter B. L. Meijer:
  Behavior Modeling by Neural Networks. 439-448
  
• Bruno Apolloni, Simone Bassis, Cristian Mesiano, Salvatore Rinaudo, Angelo Ciccazzo, Angelo Marotta:
  Statistical Parameter Identification of Analog Integrated Circuit Reverse Models. 449-458
  
• Cosmin Radu Popa:
  A New FGMOST Euclidean Distance Computational Circuit Based on Algebraic Mean of the Input Potentials. 459-466
  
• Marta Ruiz-Llata, Mar Yébenes-Calvino:
  FPGA Implementation of Support Vector Machines for 3D Object Identification. 467-474
  
• Rodrigo Martins da Silva, Nadia Nedjah, Luiza de Macedo Mourelle:
  Reconfigurable MAC-Based Architecture for Parallel Hardware Implementation on FPGAs of Artificial Neural Networks Using Fractional Fixed Point Representation. 475-484
  

Self Organization

• Jefferson R. Souza, Teresa Bernarda Ludermir, Leandro M. Almeida:
  A Two Stage Clustering Method Combining Self-Organizing Maps and Ant K-Means. 485-494
  
• Philip Prentis, Mats Sjöberg, Markus Koskela, Jorma Laaksonen:
  Image Theft Detection with Self-Organising Maps. 495-504
  
• Tomonori Shirotori, Yuko Osana:
  Improved Kohonen Feature Map Associative Memory with Area Representation for Sequential Analog Patterns. 505-514
  
• Renata L. M. E. do Rego, Hansenclever de F. Bassani, Daniel Filgueiras, Aluizio F. R. Araújo:
  Surface Reconstruction Method Based on a Growing Self-Organizing Map. 515-524
  
• Agusti Solanas, Arnau Gavalda, Robert Rallo:
  Micro-SOM: A Linear-Time Multivariate Microaggregation Algorithm Based on Self-Organizing Maps. 525-535
  
• Riccardo Rizzo, Alfonso Urso:
  Identifying Clusters Using Growing Neural Gas: First Results. 536-545
  
• Masumi Ishikawa, Kosuke Ueno:
  Hierarchical Architecture with Modular Network SOM and Modular Reinforcement Learning. 546-556
  
• Ivna Valença, Teresa Bernarda Ludermir:
  Hybrid Systems for River Flood Forecasting Using MLP, SOM and Fuzzy Systems. 557-566
  
• Nikolaos Gianniotis, Peter Tino, Steve Spreckley, Somak Raychaudhury:
  Topographic Mapping of Astronomical Light Curves via a Physically Inspired Probabilistic Model. 567-576
  
• Hujun Yin, He Ni:
  Generalized Self-Organizing Mixture Autoregressive Model for Modeling Financial Time Series. 577-586
  
• A. Ravishankar Rao, Guillermo A. Cecchi:
  Self-Organizing Map Simulations Confirm Similarity of Spatial Correlation Structure in Natural Images and Cortical Representations. 587-597
  

Intelligent Control and Adaptive Systems

• Takashi Mitsuishi, Yasunari Shidama:
  Height Defuzzification Method on L^∞ Space. 598-607
  
• Takeshi Mori, Shin Ishii:
  An Additive Reinforcement Learning. 608-617
  
• Arünas Tamasevicius, Elena Tamaseviciute, Gytis Mykolaitis, Skaidra Bumeliene, Raimundas Kirvaitis, Ruedi Stoop:
  Neural Spike Suppression by Adaptive Control of an Unknown Steady State. 618-627
  
• Naoki Tomi, Manabu Gouko, Koji Ito:
  Combined Mechanisms of Internal Model Control and Impedance Control under Force Fields. 628-637
  
• Elias B. Kosmatopoulos, Diamantis Manolis, Markos Papageorgiou:
  Neural Network Control of Unknown Nonlinear Systems with Efficient Transient Performance. 638-647
  
• Haris E. Psillakis:
  High-Order Fuzzy Switching Neural Networks: Application to the Tracking Control of a Class of Uncertain SISO Nonlinear Systems. 648-657
  

Neural and Hybrid Architectures

• Rua-Huan Tsaih, Yat-wah Wan:
  A Guide for the Upper Bound on the Number of Continuous-Valued Hidden Nodes of a Feed-Forward Network. 658-667
  
• Amit Bhaya, Fernando A. Pazos, Eugenius Kaszkurewicz:
  Comparative Study of the CG and HBF ODEs Used in the Global Minimization of Nonconvex Functions. 668-677
  
• Toshihiko Matsuka, Hidehito Honda, Arieta Chouchourelou, Sachiko Kiyokawa:
  On the Knowledge Organization in Concept Formation: An Exploratory Cognitive Modeling Study. 678-687
  
• Yoshitsugu Kakemoto, Shinichi Nakasuka:
  Dynamics of Incremental Learning by VSF-Network. 688-697
  
• Gábor Horváth, Kristóf Gáti:
  Kernel CMAC with Reduced Memory Complexity. 698-707
  
• Vera Kurková:
  Model Complexity of Neural Networks and Integral Transforms. 708-717
  
• Yevgeniy Bodyanskiy, Sergiy Popov, Mykola Titov:
  Function Decomposition Network. 718-727
  
• Stephen Hobson, Jim Austin:
  Improved Storage Capacity in Correlation Matrix Memories Storing Fixed Weight Codes. 728-736
  
• Vassilis Vassiliades, Aristodemos Cleanthous, Chris Christodoulou:
  Multiagent Reinforcement Learning with Spiking and Non-Spiking Agents in the Iterated Prisoner's Dilemma. 737-746
  
• Eric A. Antonelo, Benjamin Schrauwen:
  Unsupervised Learning in Reservoir Computing: Modeling Hippocampal Place Cells for Small Mobile Robots. 747-756
  
• Matthias Höffken, Daniel Oberhoff, Marina Kolesnik:
  Switching Hidden Markov Models for Learning of Motion Patterns in Videos. 757-766
  
• Yasuo Matsuyama, Fumiya Matsushima, Youichi Nishida, Takashi Hatakeyama, Nimiko Ochiai, Shogo Aida:
  Multimodal Belief Integration by HMM/SVM-Embedded Bayesian Network: Applications to Ambulating PC Operation by Body Motions and Brain Signals. 767-778
  
• Asuka Terai, Masanori Nakagawa:
  A Neural Network Model of Metaphor Generation with Dynamic Interaction. 779-788
  
• Wlodzislaw Duch, Tomasz Maszczyk:
  Almost Random Projection Machine. 789-798
  
• Renata M. C. R. de Souza, Telmo de M. Silva Filho:
  Optimized Learning Vector Quantization Classifier with an Adaptive Euclidean Distance. 799-806
  
• Ivan Nunes da Silva, Rogério Andrade Flauzino:
  Efficient Parametric Adjustment of Fuzzy Inference System Using Error Backpropagation Method. 807-816
  
• Marcin Korytkowski, Robert Nowicki, Rafal Scherer:
  Neuro-fuzzy Rough Classifier Ensemble. 817-823
  
• Iago Porto-Díaz, David Martínez-Rego, Amparo Alonso-Betanzos, Oscar Fontenla-Romero:
  Combining Feature Selection and Local Modelling in the KDD Cup 99 Dataset. 824-833
  
• Masato Yonekawa, Hiroaki Kurokawa:
  An Automatic Parameter Adjustment Method of Pulse Coupled Neural Network for Image Segmentation. 834-843
  
• Vladimir Kryzhanovsky:
  Pattern Identification by Committee of Potts Perceptrons. 844-853
  

Support Vector Machine

• Shigeo Abe:
  Is Primal Better Than Dual. 854-863
  
• Wataru Kasai, Yutaro Tobe, Osamu Hasegawa:
  A Fast BMU Search for Support Vector Machine. 864-873
  
• Panayiotis Ch. Andreou, Chris Charalambous, Spiros H. Martzoukos:
  European Option Pricing by Using the Support Vector Regression Approach. 874-883
  
• Guillaume Stempfel, Liva Ralaivola:
  Learning SVMs from Sloppily Labeled Data. 884-893
  
• Friedhelm Schwenker, Stefan Scherer, Yasmine M. Magdi, Günther Palm:
  The GMM-SVM Supervector Approach for the Recognition of the Emotional Status from Speech. 894-903
  
• Jorge López Lázaro, José R. Dorronsoro:
  A Simple Proof of the Convergence of the SMO Algorithm for Linearly Separable Problems. 904-912
  
• Shaoning Pang, Tao Ban, Youki Kadobayashi, Nikola K. Kasabov:
  Spanning SVM Tree for Personalized Transductive Learning. 913-922
  
• Catarina Silva, Bernardete Ribeiro:
  Improving Text Classification Performance with Incremental Background Knowledge. 923-931
  
• Vladimir Cherkassky, Wuyang Dai:
  Empirical Study of the Universum SVM Learning for High-Dimensional Data. 932-941
  
• Apostolos Marakakis, Nikolas P. Galatsanos, Aristidis Likas, Andreas Stafylopatis:
  Relevance Feedback for Content-Based Image Retrieval Using Support Vector Machines and Feature Selection. 942-951
  

Recurrent Neural Network

• Alejandro Chinea Manrique De Lara:
  Understanding the Principles of Recursive Neural Networks: A Generative Approach to Tackle Model Complexity. 952-963
  
• Jan Unkelbach, Yi Sun, Jürgen Schmidhuber:
  An EM Based Training Algorithm for Recurrent Neural Networks. 964-974
  
• Derrick Takeshi Mirikitani, Lahcen Ouarbya:
  Modeling Dst with Recurrent EM Neural Networks. 975-984
  
• David Verstraeten, Benjamin Schrauwen:
  On the Quantification of Dynamics in Reservoir Computing. 985-994
  
• Lei Zhang, Pheng-Ann Heng, Zhang Yi:
  Solving the CLM Problem by Discrete-Time Linear Threshold Recurrent Neural Networks. 995-1004
  
• Tom Schaul, Jürgen Schmidhuber:
  Scalable Neural Networks for Board Games. 1005-1014
  
• Luís A. Alexandre, Mark J. Embrechts:
  Reservoir Size, Spectral Radius and Connectivity in Static Classification Problems. 1015-1024