Multiple Classifier Systems 9th International Workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010, Proceedings
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2010, 2010
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| Edition: | 1st ed. 2010 |
| Series: | Theoretical Computer Science and General Issues
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Applications
- Forecast Combination Strategies for Handling Structural Breaks for Time Series Forecasting
- A Multiple Classifier System for Classification of LIDAR Remote Sensing Data Using Multi-class SVM
- A Multi-Classifier System for Off-Line Signature Verification Based on Dissimilarity Representation
- A Multi-objective Sequential Ensemble for Cluster Structure Analysis and Visualization and Application to Gene Expression
- Combining 2D and 3D Features to Classify Protein Mutants in HeLa Cells
- An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction
- Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network
- Invited Papers
- Some Thoughts at the Interface of Ensemble Methods and Feature Selection
- Multiple Classifier Systems for the Recogonition of Human Emotions
- Erratum
- Erratum
- Classifier Ensembles(I)
- Weighted Bagging for Graph Based One-Class Classifiers
- Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers
- New Feature Splitting Criteria for Co-training Using Genetic Algorithm Optimization
- Incremental Learning of New Classes in Unbalanced Datasets: Learn?+?+?.UDNC
- Tomographic Considerations in Ensemble Bias/Variance Decomposition
- Choosing Parameters for Random Subspace Ensembles for fMRI Classification
- Classifier Ensembles(II)
- An Experimental Study on Ensembles of Functional Trees
- Multiple Classifier Systems under Attack
- SOCIAL: Self-Organizing ClassIfier ensemble for Adversarial Learning
- Unsupervised Change-Detection in Retinal Images by a Multiple-Classifier Approach
- A Double Pruning Algorithm for Classification Ensembles
- Estimation of the Number of Clusters Using Multiple Clustering Validity Indices
- Classifier Diversity
- “Good” and “Bad” Diversity in Majority Vote Ensembles
- Multi-information Ensemble Diversity
- Classifier Selection
- Dynamic Selection of Ensembles of Classifiers Using Contextual Information
- Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems
- Combining Multiple Kernels
- A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities
- Combining Multiple Kernels by Augmenting the Kernel Matrix
- Boosting and Bootstrapping
- Class-Separability Weighting and Bootstrapping in Error Correcting Output Code Ensembles
- Boosted Geometry-Based Ensembles
- Online Non-stationary Boosting
- Handwriting Recognition
- Combining Neural Networks to Improve Performance of Handwritten Keyword Spotting
- Combining Committee-Based Semi-supervised and Active Learning and Its Application toHandwritten Digits Recognition
- Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition