7. MCS 2007: Prague, Czech Republic

Kernel-Based Fusion

• Vadim Mottl, Alexander Tatarchuk, Valentina Sulimova, Olga Krasotkina, Oleg Seredin:
  Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion. 1-12
  
• David Windridge, Vadim Mottl, Alexander Tatarchuk, Andrey Eliseyev:
  The Neutral Point Method for Kernel-Based Combination of Disjoint Training Data in Multi-modal Pattern Recognition. 13-21
  
• Wan-Jui Lee, Sergey Verzakov, Robert P. W. Duin:
  Kernel Combination Versus Classifier Combination. 22-31
  
• Stefano Merler, Giuseppe Jurman, Cesare Furlanello:
  Deriving the Kernel from Training Data. 32-41
  

Applications

• Kai Lienemann, Thomas Plötz, Gernot A. Fink:
  On the Application of SVM-Ensembles Based on Adapted Random Subspace Sampling for Automatic Classification of NMR Data. 42-51
  
• Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souza Britto Jr.:
  A New HMM-Based Ensemble Generation Method for Numeral Recognition. 52-61
  
• Sarunas Raudys, Ömer Kaan Baykan, Ahmet Babalik, Vitalij Denisov, Antanas Andrius Bielskis:
  Classifiers Fusion in Recognition of Wheat Varieties. 62-71
  
• Roman Bertolami, Horst Bunke:
  Multiple Classifier Methods for Offline Handwritten Text Line Recognition. 72-81
  
• Hans Ulrich Christensen, Daniel Ortiz Arroyo:
  Applying Data Fusion Methods to Passage Retrieval in QAS. 82-92
  
• Tawfik A. Mohamed, Neamat El Gayar, Amir F. Atiya:
  A Co-training Approach for Time Series Prediction with Missing Data. 93-102
  
• Shiliang Sun:
  An Improved Random Subspace Method and Its Application to EEG Signal Classification. 103-112
  
• Shiliang Sun:
  Ensemble Learning Methods for Classifying EEG Signals. 113-120
  
• Mohammad Sadeghi, Samaneh Khoshrou, Josef Kittler:
  Confidence Based Gating of Colour Features for Face Authentication. 121-130
  
• Reza Ebrahimpour, Ehsanollah Kabir, Mohammad Reza Yousefi:
  View-Based Eigenspaces with Mixture of Experts for View-Independent Face Recognition. 131-140
  
• Ángel Serrano, Isaac Martín de Diego, Cristina Conde, Enrique Cabello, Li Bai, LinLin Shen:
  Fusion of Support Vector Classifiers for Parallel Gabor Methods Applied to Face Verification. 141-150
  
• Gian Luca Marcialis, Fabio Roli:
  Serial Fusion of Fingerprint and Face Matchers. 151-160
  

Boosting

• Lawrence O. Hall, Robert E. Banfield, Kevin W. Bowyer, W. Philip Kegelmeyer:
  Boosting Lite - Handling Larger Datasets and Slower Base Classifiers. 161-170
  
• Julien Meynet, Jean-Philippe Thiran:
  Information Theoretic Combination of Classifiers with Application to AdaBoost. 171-179
  
• Yijuan Lu, Qi Tian, Thomas S. Huang:
  Interactive Boosting for Image Classification. 180-189
  

Cluster and Graph Ensembles

• Manuele Bicego, Elzbieta Pekalska, Robert P. W. Duin:
  Group-Induced Vector Spaces. 190-199
  
• Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva:
  Selecting Diversifying Heuristics for Cluster Ensembles. 200-209
  
• Michal Haindl, Stanislav Mikes:
  Unsupervised Texture Segmentation Using Multiple Segmenters Strategy. 210-219
  
• Kaspar Riesen, Horst Bunke:
  Classifier Ensembles for Vector Space Embedding of Graphs. 220-230
  
• Jesús Maudes, Juan José Rodríguez, Cesar García-Osorio:
  Cascading for Nominal Data. 231-240
  

Feature Subspace Ensembles

• Mineichi Kudo, Satoshi Shirai, Hiroshi Tenmoto:
  A Combination of Sample Subsets and Feature Subsets in One-Against-Other Classifiers. 241-250
  
• Joseph DePasquale, Robi Polikar:
  Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features. 251-260
  
• Hugo Silva, Ana L. N. Fred:
  Feature Subspace Ensembles: A Parallel Classifier Combination Scheme Using Feature Selection. 261-270
  
• Terry Windeatt, Matthew Prior:
  Stopping Criteria for Ensemble-Based Feature Selection. 271-281
  

Multiple Classifier System Theory

• Pasquale Foggia, Gennaro Percannella, Carlo Sansone, Mario Vento:
  On Rejecting Unreliably Classified Patterns. 282-291
  
• Battista Biggio, Giorgio Fumera, Fabio Roli:
  Bayesian Analysis of Linear Combiners. 292-301
  
• Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souza Britto Jr.:
  Applying Pairwise Fusion Matrix on Fusion Functions for Classifier Combination. 302-311
  
• Samuel Chindaro, Konstantinos Sirlantzis, Michael C. Fairhurst:
  Modelling Multiple-Classifier Relationships Using Bayesian Belief Networks. 312-321
  
• Shoushan Li, Chengqing Zong:
  Classifier Combining Rules Under Independence Assumptions. 322-332
  
• Claudio Marrocco, Paolo Simeone, Francesco Tortorella:
  Embedding Reject Option in ECOC Through LDPC Codes. 333-343
  

Intramodal and Multimodal Fusion of Biometric Experts

• Norman Poh, Guillaume Heusch, Josef Kittler:
  On Combination of Face Authentication Experts by a Mixture of Quality Dependent Fusion Classifiers. 344-356
  
• Roberto Tronci, Giorgio Giacinto, Fabio Roli:
  Index Driven Combination of Multiple Biometric Experts for AUC Maximisation. 357-366
  
• Krzysztof Kryszczuk, Andrzej Drygajlo:
  Q-stack: Uni- and Multimodal Classifier Stacking with Quality Measures. 367-376
  
• Jonas Richiardi, Andrzej Drygajlo:
  Reliability-Based Voting Schemes Using Modality-Independent Features in Multi-classifier Biometric Authentication. 377-386
  
• Sergey Tulyakov, Venu Govindaraju, Chaohong Wu:
  Optimal Classifier Combination Rules for Verification and Identification Systems. 387-396
  

Majority Voting

• Nitesh V. Chawla, Jared Sylvester:
  Exploiting Diversity in Ensembles: Improving the Performance on Unbalanced Datasets. 397-406
  
• Yun Sheng Chung, D. Frank Hsu, Chuan Yi Tang:
  On the Diversity-Performance Relationship for Majority Voting in Classifier Ensembles. 407-420
  
• Hubert Cecotti, Abdel Belaïd:
  Hierarchical Behavior Knowledge Space. 421-430
  

Ensemble Learning

• Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souza Britto Jr.:
  A New Dynamic Ensemble Selection Method for Numeral Recognition. 431-439
  
• Manuela Zanda, Gavin Brown, Giorgio Fumera, Fabio Roli:
  Ensemble Learning in Linearly Combined Classifiers Via Negative Correlation. 440-449
  
• Juan José Rodríguez, Ludmila I. Kuncheva:
  Naïve Bayes Ensembles with a Random Oracle. 450-458
  
• Ludmila I. Kuncheva, Juan José Rodríguez:
  An Experimental Study on Rotation Forest Ensembles. 459-468
  
• Daniel Kanevskiy, Konstantin Vorontsov:
  Cooperative Coevolutionary Ensemble Learning. 469-478
  
• Omer Berkman, Nathan Intrator:
  Robust Inference in Bayesian Networks with Application to Gene Expression Temporal Data. 479-489
  
• Michael Muhlbaier, Robi Polikar:
  An Ensemble Approach for Incremental Learning in Nonstationary Environments. 490-500
  

Invited Papers

• Jon Atli Benediktsson, Jocelyn Chanussot, Mathieu Fauvel:
  Multiple Classifier Systems in Remote Sensing: From Basics to Recent Developments. 501-512
  
• Samy Bengio, Johnny Mariéthoz:
  Biometric Person Authentication Is a Multiple Classifier Problem. 513-522
  

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