Buch, Englisch, Band 7553, 590 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 920 g
22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II
Buch, Englisch, Band 7553, 590 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 920 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-642-33265-4
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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 ß-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 RelationalData 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.
