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8. MCS 2009: Reykjavik, Iceland
- Jón Atli Benediktsson, Josef Kittler, Fabio Roli:
Multiple Classifier Systems, 8th International Workshop, MCS 2009, Reykjavik, Iceland, June 10-12, 2009. Proceedings. Lecture Notes in Computer Science 5519, Springer 2009, ISBN 978-3-642-02325-5
ECOC, Boosting and Bagging
- Raymond S. Smith, Terry Windeatt
:
The Bias Variance Trade-Off in Bootstrapped Error Correcting Output Code Ensembles. 1-10 - Sergio Escalera
Recoding Error-Correcting Output Codes. 11-21 - Satoshi Shirai, Mineichi Kudo
Comparison of Bagging and Boosting Algorithms on Sample and Feature Weighting. 22-31 - Goo Jun
Multi-class Boosting with Class Hierarchies. 32-41 - Goo Jun
Hybrid Hierarchical Classifiers for Hyperspectral Data Analysis. 42-51
MCS in Remote Sensing
- Peijun Du
Multiple Classifier Combination for Hyperspectral Remote Sensing Image Classification. 52-61 - Xavier Ceamanos, Björn Waske
Ensemble Strategies for Classifying Hyperspectral Remote Sensing Data. 62-71
Unbalanced Data and Decision Templates
- David M. J. Tax, Marco Loog, Robert P. W. Duin:
Optimal Mean-Precision Classifier. 72-81 - Muhammad Atif Tahir, Josef Kittler, Krystian Mikolajczyk, Fei Yan:
A Multiple Expert Approach to the Class Imbalance Problem Using Inverse Random under Sampling. 82-91 - Mohamed Farouk Abdel Hady, Friedhelm Schwenker:
Decision Templates Based RBF Network for Tree-Structured Multiple Classifier Fusion. 92-101
Stacked Generalization and Active Learning
- Narayanan Unny Edakunni
Efficient Online Classification Using an Ensemble of Bayesian Linear Logistic Regressors. 102-111 - Samuel Robert Reid, Gregory Z. Grudic:
Regularized Linear Models in Stacked Generalization. 112-121 - Davy Sannen, Hendrik Van Brussel:
Active Grading Ensembles for Learning Visual Quality Control from Multiple Humans. 122-131 - Battista Biggio
Multiple Classifier Systems for Adversarial Classification Tasks. 132-141
Concept Drift, Missing Values and Random Forest
- Ryan Elwell, Robi Polikar
Incremental Learning of Variable Rate Concept Drift. 142-151 - Luca Didaci
Semi-supervised Co-update of Multiple Matchers. 152-160 - David Windridge
Handling Multimodal Information Fusion with Missing Observations Using the Neutral Point Substitution Method. 161-170 - Simon Bernard
Influence of Hyperparameters on Random Forest Accuracy. 171-180
SVM Ensembles
- Albert D. Shieh, David F. Kamm:
Ensembles of One Class Support Vector Machines. 181-190 - Jesús Maudes
Disturbing Neighbors Ensembles for Linear SVM. 191-200
Fusion of Graphs, Concepts and Categorical Data
- Wan-Jui Lee, Robert P. W. Duin:
A Labelled Graph Based Multiple Classifier System. 201-210 - Kaspar Riesen
Cluster Ensembles Based on Vector Space Embeddings of Graphs. 211-221 - Amir Ahmad, Gavin Brown:
Random Ordinality Ensembles A Novel Ensemble Method for Multi-valued Categorical Data. 222-231 - Giorgio Valentini
True Path Rule Hierarchical Ensembles. 232-241
Clustering
- Manuela Zanda, Gavin Brown:
A Study of Semi-supervised Generative Ensembles. 242-251 - Mingmin Chi, Youdong Miao, Youze Tang, Jón Atli Benediktsson
Hierarchical Ensemble Support Cluster Machine. 252-261 - Oriol Pujol
Multi-scale Stacked Sequential Learning. 262-271 - Michal Haindl
Unsupervised Hierarchical Weighted Multi-segmenter. 272-282 - Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof:
Ant Clustering Using Ensembles of Partitions. 283-292
Classifier and Feature Selection
- Nan Li, Zhi-Hua Zhou:
Selective Ensemble under Regularization Framework. 293-303 - Petr Somol, Jirí Grim, Pavel Pudil
Criteria Ensembles in Feature Selection. 304-313 - Francesco Gargiulo
Network Protocol Verification by a Classifier Selection Ensemble. 314-323 - Alexander Tatarchuk, Valentina Sulimova, David Windridge
Supervised Selective Combining Pattern Recognition Modalities and Its Application to Signature Verification by Fusing On-Line and Off-Line Kernels. 324-334
Theory of MCS
- Matthew Prior, Terry Windeatt:
Improved Uniformity Enforcement in Stochastic Discrimination. 335-343 - Gavin Brown:
An Information Theoretic Perspective on Multiple Classifier Systems. 344-353 - Amber Tomas:
Constraints in Weighted Averaging. 354-363 - Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng
FaSS: Ensembles for Stable Learners. 364-374
MCS Methods and Applications
- Björn Waske
Classifying Remote Sensing Data with Support Vector Machines and Imbalanced Training Data. 375-384 - Michael J. Procopio, W. Philip Kegelmeyer, Gregory Z. Grudic, Jane Mulligan:
Terrain Segmentation with On-Line Mixtures of Experts for Autonomous Robot Navigation. 385-397 - Peijun Du
Consistency Measure of Multiple Classifiers for Land Cover Classification by Remote Sensing Image. 398-407 - Peijun Du
Target Identification from High Resolution Remote Sensing Image by Combining Multiple Classifiers. 408-417 - Sergey Tulyakov, Venu Govindaraju
Neural Network Optimization for Combinations in Identification Systems. 418-427 - Waleed M. Azmy, Neamat El Gayar
MLP, Gaussian Processes and Negative Correlation Learning for Time Series Prediction. 428-437 - Ingrid Visentini, Josef Kittler, Gian Luca Foresti:
Diversity-Based Classifier Selection for Adaptive Object Tracking. 438-447 - Matteo Re
Ensemble Based Data Fusion for Gene Function Prediction. 448-457 - Jian-Wu Xu, Vartika Singh, Venu Govindaraju
A Cascade Multiple Classifier System for Document Categorization. 458-467 - Marco Loog, Yan Li, David M. J. Tax:
Maximum Membership Scale Selection. 468-477 - Chunxia Zhang, Robert P. W. Duin:
An Empirical Study of a Linear Regression Combiner on Multi-class Data Sets. 478-487 - Amir Ahmad, Gavin Brown:
A Study of Random Linear Oracle Ensembles. 488-497 - Kai Lienemann, Thomas Plötz, Gernot A. Fink
Stacking for Ensembles of Local Experts in Metabonomic Applications. 498-508 - Kai Ming Ting, Lian Zhu:
Boosting Support Vector Machines Successfully. 509-518
Invited Papers
- Melba M. Crawford, Wonkook Kim:
Manifold Learning for Multi-classifier Systems via Ensembles. 519-528 - Zhi-Hua Zhou:
When Semi-supervised Learning Meets Ensemble Learning. 529-538
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