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 N. 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, Luís 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, Hsin Chen: Current-Mode Computation with Noise in a Scalable and Programmable Probabilistic Neural VLSI System. 401-409
• 
  Chih-Cheng Lu, Hsin 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, Manolis Diamantis, 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 Agustin 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

last updated on Sat May 18 05:00:01 2013 by the dblp team
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