| Description |
1 online resource |
| Series |
Lecture notes in computer science, 0302-9743 ; 7553 |
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LNCS sublibrary. SL 1, Theoretical computer science and general issues |
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Lecture notes in computer science ; 7553.
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LNCS sublibrary. SL 1, Theoretical computer science and general issues.
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| Contents |
880-01 Complex-Valued Multilayer Perceptron Search Utilizing Eigen Vector Descent and Reducibility Mapping / Shinya Suzumura and Ryohei Nakano -- Theoretical Analysis of Function of Derivative Term in On-Line Gradient Descent Learning / Kazuyuki Hara, Kentaro Katahira, Kazuo Okanoya and Masato Okada -- Some Comparisons of Networks with Radial and Kernel Units / Věra Kůrková -- Multilayer Perceptron for Label Ranking / Geraldina Ribeiro, Wouter Duivesteijn, Carlos Soares and Arno Knobbe -- Electricity Load Forecasting: A Weekday-Based Approach / Irena Koprinska, Mashud Rana and Vassilios G. Agelidis -- Adaptive Exploration Using Stochastic Neurons / Michel Tokic and Günther Palm -- Comparison of Long-Term Adaptivity for Neural Networks / Frank-Florian Steege and Horst-Michael Groß -- Simplifying ConvNets for Fast Learning / Franck Mamalet and Christophe Garcia -- A Modified Artificial Fish Swarm Algorithm for the Optimization of Extreme Learning Machines / João Fausto Lorenzato de Oliveira and Teresa B. Ludermir -- Robust Training of Feedforward Neural Networks Using Combined Online/Batch Quasi-Newton Techniques / Hiroshi Ninomiya -- Estimating a Causal Order among Groups of Variables in Linear Models / Doris Entner and Patrik O. Hoyer -- Training Restricted Boltzmann Machines with Multi-tempering: Harnessing Parallelization / Philemon Brakel, Sander Dieleman and Benjamin Schrauwen |
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880-01/(S Complex-Valued Multilayer Perceptron Search Utilizing Eigen Vector Descent and Reducibility -- Theoretical Analysis of Function of Derivative Term in On-Line Gradient Descent Learning -- Some Comparisons of Networks with Radial and Kernel -- Multilayer Perceptron for Label Ranking -- Electricity Load Forecasting: A Weekday-Based -- Adaptive Exploration Using Stochastic Neurons -- Comparison of Long-Term Adaptivity for Neural Networks -- Simplifying ConvNets for Fast Learning -- A Modified Artificial Fish Swarm Algorithm for the Optimization of Extreme Learning Machines -- Robust Training of Feedforward Neural Networks Using Combined Online/Batch Quasi-Newton Techniques -- Estimating a Causal Order among Groups of Variables in Linear Models -- Training Restricted Boltzmann Machines with Multi-tempering: Harnessing Parallelization -- A Computational Geometry Approach for Pareto-Optimal Selection of Neural Networks -- Learning Parameters of Linear Models in Compressed Parameter Space -- Control of a Free-Falling Cat by Policy-Based Reinforcement Learning -- Gated Boltzmann Machine in Texture Modeling -- Neural PCA and Maximum Likelihood Hebbian Learning on the GPU -- Construction of Emerging Markets Exchange Traded Funds Using Multiobjective Particle Swarm Optimisation -- The Influence of Supervised Clustering for RBFNN Centers Definition: A Comparative Study -- Nested Sequential Minimal Optimization for Support Vector Machines -- Random Subspace Method and Genetic Algorithm Applied to a LS-SVM Ensemble -- Text Recognition in Videos Using a Recurrent Connectionist Approach -- An Investigation of Ensemble Systems Applied to Encrypted and Cancellable Biometric Data -- New Dynamic Classifiers Selection Approach for Handwritten Recognition -- Vector Perceptron Learning Algorithm Using Linear Programming -- TrueSkill-Based Pairwise Coupling for Multi-class Classification -- Analogical Inferences in the Family Trees Task: A Review -- An Efficient Way of Combining SVMs for Handwritten Digit Recognition -- Comparative Evaluation of Regression Methods for 3D-2D Image Registration -- A MDRNN-SVM Hybrid Model for Cursive Offline Handwriting Recognition -- Extraction of Prototype-Based Threshold Rules Using Neural Training Procedure -- Instance Selection with Neural Networks for Regression Problems -- A New Distance for Probability Measures Based on the Estimation of Level Sets -- Low Complexity Proto-Value Function Learning from Sensory Observations with Incremental Slow Feature Analysis -- Improving Neural Networks Classification through Chaining -- Feature Ranking Methods Used for Selection of Prototypes -- A "Learning from Models" Cognitive Fault Diagnosis System -- Improving ANNs Performance on Unbalanced Data with an AUC-Based Learning Algorithm -- Learning Using Privileged Information in Prototype Based Models -- A Sparse Support Vector Machine Classifier with Nonparametric Discriminants -- Training Mahalanobis Kernels by Linear Programming -- Correntropy-Based Document Clustering via Nonnegative Matrix Factorization -- SOMM -- Self-Organized Manifold Mapping -- Self-Organizing Map and Tree Topology for Graph Summarization -- Variable-Sized Kohonen Feature Map Probabilistic Associative Memory -- Learning Deep Belief Networks from Non-stationary Streams -- Separation and Unification of Individuality and Collectivity and Its Application to Explicit Class Structure in Self-Organizing Maps -- Autoencoding Ground Motion Data for Visualisation -- Examining an Evaluation Mechanism of Metaphor Generation with Experiments and Computational Model Simulation -- Pairwise Clustering with t-PLSI -- Selecting β-Divergence for Nonnegative Matrix Factorization by Score Matching -- Neural Networks for Proof-Pattern Recognition -- Using Weighted Clustering and Symbolic Data to Evaluate Institutes Scientific Production -- Comparison of Input Data Compression Methods in Neural Network Solution of Inverse Problem in Laser Raman Spectroscopy of Natural Waters -- New Approach for Clustering Relational Data Based on Relationship and Attribute Information -- Comparative Study on Information Theoretic Clustering and Classical Clustering Algorithms -- Text Mining for Wellbeing: Selecting Stories Using Semantic and Pragmatic Features -- Hybrid Bilinear and Trilinear Models for Exploratory Analysis of Three-Way Poisson Counts -- and Machine Learning Algorithms -- Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets -- Using a Support Vector Machine and Sampling to Classify Compounds as Potential Transdermal Enhancers -- The Application of Gaussian Processes in the Predictions of Permeability across Mammalian Membranes -- Protein Structural Blocks Representation and Search through Unsupervised NN -- Evolutionary Support Vector Machines for Time Series Forecasting -- Learning Relevant Time Points for Time-Series Data in the Life Sciences -- A Multivariate Approach to Estimate Complexity of FMRI Time Series -- Neural Architectures for Global Solar Irradiation and Air Temperature Prediction -- Sparse Linear Wind Farm Energy Forecast -- Diffusion Maps and Local Models for Wind Power Prediction -- A Hybrid Model for S&P500 Index Forecasting |
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A Computational Geometry Approach for Pareto-Optimal Selection of Neural Networks / Luiz C.B. Torres, Cristiano L. Castro and Antônio P. Braga -- Learning Parameters of Linear Models in Compressed Parameter Space / Yohannes Kassahun, Hendrik Wöhrle, Alexander Fabisch and Marc Tabie -- Control of a Free-Falling Cat by Policy-Based Reinforcement Learning / Daichi Nakano, Shin-ichi Maeda and Shin Ishii -- Gated Boltzmann Machine in Texture Modeling / Tele Hao, Tapani Raiko, Alexander Ilin and Juha Karhunen -- Neural PCA and Maximum Likelihood Hebbian Learning on the GPU / Pavel Krömer, Emilio Corchado, Václav Snášel, Jan Platoš and Laura García-Hernández -- Construction of Emerging Markets Exchange Traded Funds Using Multiobjective Particle Swarm Optimisation / Marta Díez-Fernández, Sergio Alvarez Teleña and Denise Gorse -- The Influence of Supervised Clustering for RBFNN Centers Definition: A Comparative Study / André R. Gonçalves, Rosana Veroneze, Salomão Madeiro, Carlos R.B. Azevedo and Fernando J. Von Zuben -- Nested Sequential Minimal Optimization for Support Vector Machines / Alessandro Ghio, Davide Anguita, Luca Oneto, Sandro Ridella and Carlotta Schatten -- Random Subspace Method and Genetic Algorithm Applied to a LS-SVM Ensemble / Carlos Padilha, Adrião Dória Neto and Jorge Melo |
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Text Recognition in Videos Using a Recurrent Connectionist Approach / Khaoula Elagouni, Christophe Garcia, Franck Mamalet and Pascale Sébillot -- An Investigation of Ensemble Systems Applied to Encrypted and Cancellable Biometric Data / Isaac de L. Oliveira Filho, Benjamn R.C. Bedregal and Anne M.P. Canuto -- New Dynamic Classifiers Selection Approach for Handwritten Recognition / Nabiha Azizi, Nadir Farah and Abdel Ennaji -- Vector Perceptron Learning Algorithm Using Linear Programming / Vladimir Kryzhanovskiy, Irina Zhelavskaya and Anatoliy Fonarev -- A Robust Objective Function of Joint Approximate Diagonalization / Yoshitatsu Matsuda and Kazunori Yamaguchi -- TrueSkill-Based Pairwise Coupling for Multi-class Classification / Jong-Seok Lee -- Analogical Inferences in the Family Trees Task: A Review / Sergio Varona-Moya and Pedro L. Cobos -- An Efficient Way of Combining SVMs for Handwritten Digit Recognition / Renata F.P. Neves, Cleber Zanchettin and Alberto N.G. Lopes Filho -- Comparative Evaluation of Regression Methods for 3D-2D Image Registration / Ana Isabel Rodrigues Gouveia, Coert Metz, Luís Freire and Stefan Klein -- A MDRNN-SVM Hybrid Model for Cursive Offline Handwriting Recognition / Byron Leite Dantas Bezerra, Cleber Zanchettin and Vinícius Braga de Andrade -- Extraction of Prototype-Based Threshold Rules Using Neural Training Procedure / Marcin Blachnik, Mirosław Kordos and Włodzisław Duch |
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Instance Selection with Neural Networks for Regression Problems / Mirosław Kordos and Marcin Blachnik -- A New Distance for Probability Measures Based on the Estimation of Level Sets / Alberto Muñoz, Gabriel Martos, Javier Arriero and Javier Gonzalez -- Low Complexity Proto-Value Function Learning from Sensory Observations with Incremental Slow Feature Analysis / Matthew Luciw and Juergen Schmidhuber -- Improving Neural Networks Classification through Chaining / Khobaib Zaamout and John Z. Zhang -- Feature Ranking Methods Used for Selection of Prototypes / Marcin Blachnik, Włodzisław Duch and Tomasz Maszczyk -- A "Learning from Models" Cognitive Fault Diagnosis System / Cesare Alippi, Manuel Roveri and Francesco Trovò -- Improving ANNs Performance on Unbalanced Data with an AUC-Based Learning Algorithm / Cristiano L. Castro and Antônio P. Braga -- Learning Using Privileged Information in Prototype Based Models / Shereen Fouad, Peter Tino, Somak Raychaudhury and Petra Schneider -- A Sparse Support Vector Machine Classifier with Nonparametric Discriminants / Naimul Mefraz Khan, Riadh Ksantini, Imran Shafiq Ahmad and Ling Guan -- Training Mahalanobis Kernels by Linear Programming / Shigeo Abe -- Correntropy-Based Document Clustering via Nonnegative Matrix Factorization / Tolga Ensari, Jan Chorowski and Jacek M. Zurada |
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SOMM -- Self-Organized Manifold Mapping / Edson Caoru Kitani, Emilio Del-Moral-Hernandez and Leandro A. Silva -- Self-Organizing Map and Tree Topology for Graph Summarization / Nhat-Quang Doan, Hanane Azzag and Mustapha Lebbah -- Variable-Sized Kohonen Feature Map Probabilistic Associative Memory / Hiroki Sato and Yuko Osana -- Learning Deep Belief Networks from Non-stationary Streams / Roberto Calandra, Tapani Raiko, Marc Peter Deisenroth and Federico Montesino Pouzols -- Separation and Unification of Individuality and Collectivity and Its Application to Explicit Class Structure in Self-Organizing Maps / Ryotaro Kamimura -- Autoencoding Ground Motion Data for Visualisation / Nikolaos Gianniotis, Carsten Riggelsen, Nicolas Kühn and Frank Scherbaum -- Examining an Evaluation Mechanism of Metaphor Generation with Experiments and Computational Model Simulation / Asuka Terai, Keiga Abe and Masanori Nakagawa -- Pairwise Clustering with t-PLSI / He Zhang, Tele Hao, Zhirong Yang and Erkki Oja -- Selecting [beta]-Divergence for Nonnegative Matrix Factorization by Score Matching / Zhiyun Lu, Zhirong Yang and Erkki Oja -- Neural Networks for Proof-Pattern Recognition / Ekaterina Komendantskaya and Kacper Lichota -- Using Weighted Clustering and Symbolic Data to Evaluate Institutes's Scientific Production / Bruno Almeida Pimentel, Jarley P. Nóbrega and Renata M.C.R. de Souza |
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Comparison of Input Data Compression Methods in Neural Network Solution of Inverse Problem in Laser Raman Spectroscopy of Natural Waters / Sergey Dolenko, Tatiana Dolenko, Sergey Burikov, Victor Fadeev and Alexey Sabirov, et al. -- New Approach for Clustering Relational Data Based on Relationship and Attribute Information / João Carlos Xavier-Júnior, Anne M.P. Canuto, Luiz M.G. Gonçalves and Luiz A.H.G. de Oliveira -- Comparative Study on Information Theoretic Clustering and Classical Clustering Algorithms / Daniel Araújo, Adrião Dória Neto and Allan Martins -- Text Mining for Wellbeing: Selecting Stories Using Semantic and Pragmatic Features / Timo Honkela, Zaur Izzatdust and Krista Lagus -- Hybrid Bilinear and Trilinear Models for Exploratory Analysis of Three-Way Poisson Counts / Juha Raitio, Tapani Raiko and Timo Honkela -- Estimating Quantities: Comparing Simple Heuristics and Machine Learning Algorithms / Jan K. Woike, Ulrich Hoffrage and Ralph Hertwig -- Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets / Luca Oneto, Davide Anguita, Alessandro Ghio and Sandro Ridella -- Using a Support Vector Machine and Sampling to Classify Compounds as Potential Transdermal Enhancers / Alpa Shah, Gary P. Moss, Yi Sun, Rod Adams and Neil Davey, et al |
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The Application of Gaussian Processes in the Predictions of Permeability across Mammalian Membranes / Yi Sun, Marc B. Brown, Maria Prapopoulou, Rod Adams and Neil Davey, et al. -- Protein Structural Blocks Representation and Search through Unsupervised NN / Virginio Cantoni, Alessio Ferone, Ozlem Ozbudak and Alfredo Petrosino -- Evolutionary Support Vector Machines for Time Series Forecasting / Paulo Cortez and Juan Peralta Donate -- Learning Relevant Time Points for Time-Series Data in the Life Sciences / Frank-Michael Schleif, Bassam Mokbel, Andrej Gisbrecht, Leslie Theunissen and Volker Dürr, et al. -- A Multivariate Approach to Estimate Complexity of FMRI Time Series / Henry Schütze, Thomas Martinetz, Silke Anders and Amir Madany Mamlouk -- Neural Architectures for Global Solar Irradiation and Air Temperature Prediction / Pierrick Bruneau, Laurence Boudet and Cécilia Damon -- Sparse Linear Wind Farm Energy Forecast / Carlos M. Alaíz, Alberto Torres and José R. Dorronsoro -- Diffusion Maps and Local Models for Wind Power Prediction / Ángela Fernández Pascual, Carlos M. Alaíz, Ana Ma González Marcos, Julia Díaz García and José R. Dorronsoro -- A Hybrid Model for S & P500 Index Forecasting / Ricardo de A. Araújo, Adriano L.I. Oliveira and Silvio R.L. Meira |
| Summary |
The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting |
| Analysis |
Computer science |
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Computer software |
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Artificial intelligence |
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Computer vision |
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Optical pattern recognition |
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Algorithm Analysis and Problem Complexity |
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Pattern Recognition |
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Image Processing and Computer Vision |
| Notes |
International conference proceedings |
| Bibliography |
Includes bibliographical references and author index |
| Subject |
Neural networks (Computer science) -- Congresses
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Machine learning -- Congresses
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Informatique.
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Machine learning
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Neural networks (Computer science)
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| Genre/Form |
Conference papers and proceedings
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Software.
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| Form |
Electronic book
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| Author |
Villa, Alessandro E. P
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| ISBN |
9783642332661 |
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3642332668 |
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