Vor Ort
Merkzettel Warenkorb
  • Produktbild: Artificial Neural Networks and Machine Learning -- ICANN 2012
  • Produktbild: Artificial Neural Networks and Machine Learning -- ICANN 2012
Band 7553

Artificial Neural Networks and Machine Learning -- ICANN 2012 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II

Aus der Reihe Theoretical Computer Science and General Issues

51,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

08.08.2012

Abbildungen

XXVIII, 590 p. 172 illus.

Herausgeber

Alessandro Villa + weitere

Verlag

Springer Berlin

Seitenzahl

590

Maße (L/B/H)

23,5/15,5/3,3 cm

Gewicht

920 g

Auflage

2012

Sprache

Englisch

ISBN

978-3-642-33265-4

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

08.08.2012

Abbildungen

XXVIII, 590 p. 172 illus.

Herausgeber

Verlag

Springer Berlin

Seitenzahl

590

Maße (L/B/H)

23,5/15,5/3,3 cm

Gewicht

920 g

Auflage

2012

Sprache

Englisch

ISBN

978-3-642-33265-4

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: Artificial Neural Networks and Machine Learning -- ICANN 2012
  • Produktbild: Artificial Neural Networks and Machine Learning -- ICANN 2012
  • Complex-Valued Multilayer Perceptron Search Utilizing Eigen VectorDescent 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 CombinedOnline/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 Selectionof 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 UsingMultiobjective 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 ImageRegistration.- A MDRNN-SVM Hybrid Model for Cursive Offline HandwritingRecognition.- 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 NonparametricDiscriminants.- Training Mahalanobis Kernels by Linear Programming.- Correntropy-Based Document Clustering via Nonnegative MatrixFactorization.- 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 Generationwith 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 InstitutesScientific 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 ofThree-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.