Artificial Neural Networks and Machine Learning -- ICANN 2012 : 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II / edited by Alessandro Villa, Włodzisław Duch, Péter Érdi, Francesco Masulli, Günther Palm.

Format:

Book

Contributor:

Villa, Alessandro, Editor.

Duch, Włodzisław., Editor.

Érdi, Péter, Editor.

Masulli, F. (Francesco), Editor.

Palm, Günther, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Theoretical computer science and general issues 2512-2029 ; SL 1, 7553

Theoretical Computer Science and General Issues, 2512-2029 ; 7553

Language:

English

Subjects (All):

Artificial intelligence.

Computer science.

Algorithms.

Pattern recognition systems.

Application software.

Computer vision.

Artificial Intelligence.

Theory of Computation.

Automated Pattern Recognition.

Computer and Information Systems Applications.

Computer Vision.

Local Subjects:

Artificial Intelligence.

Theory of Computation.

Algorithms.

Automated Pattern Recognition.

Computer and Information Systems Applications.

Computer Vision.

Physical Description:

1 online resource (XXVIII, 590 pages) : 172 illustrations

Edition:

1st ed. 2012.

Contained In:

Springer Nature eBook

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.

System Details:

text file PDF

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-642-33266-1

9783642332661

Access Restriction:

Restricted for use by site license.