5. MCS 2004: Cagliari, Italy

Invited Papers

• Ludmila I. Kuncheva:
  Classifier Ensembles for Changing Environments. 1-15
  
• Nageswara S. V. Rao:
  A Generic Sensor Fusion Problem: Classification and Function Estimation. 16-30
  

Bagging and Boosting

• Nikunj C. Oza:
  AveBoost2: Boosting for Noisy Data. 31-40
  
• Vicent Estruch, César Ferri, José Hernández-Orallo, M. José Ramírez-Quintana:
  Bagging Decision Multi-trees. 41-51
  
• Michael Muhlbaier, Apostolos Topalis, Robi Polikar:
  Learn++.MT: A New Approach to Incremental Learning. 52-61
  
• Elizabeth Tapia, José Carlos González, Alexander Hüntemann, L. Javier García-Villalba:
  Beyond Boosting: Recursive ECOC Learning Machines. 62-71
  
• Bruno Caprile, Stefano Merler, Cesare Furlanello, Giuseppe Jurman:
  Exact Bagging with k-Nearest Neighbour Classifiers. 72-81
  

Combination Methods

• Marco Saerens, François Fouss:
  Yet Another Method for Combining Classifiers Outputs: A Maximum Entropy Approach. 82-91
  
• Piotr Juszczak, Robert P. W. Duin:
  Combining One-Class Classifiers to Classify Missing Data. 92-101
  
• Isaac Martín de Diego, Javier M. Moguerza, Alberto Muñoz:
  Combining Kernel Information for Support Vector Classification. 102-111
  
• Hee-Joong Kang:
  Combining Classifiers Using Dependency-Based Product Approximation with Bayes Error Rate. 112-121
  
• Elzbieta Pekalska, Marina Skurichina, Robert P. W. Duin:
  Combining Dissimilarity-Based One-Class Classifiers. 122-133
  
• Lei Chen, Mohamed Kamel, Ju Jiang:
  A Modular System for the Classification of Time Series Data. 134-143
  
• Hanan Ayad, Otman A. Basir, Mohamed Kamel:
  A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles. 144-153
  
• Piero P. Bonissone, Kai Goebel, Weizhong Yan:
  Classifier Fusion Using Triangular Norms. 154-163
  
• Niall Rooney, David W. Patterson, Sarab S. Anand, Alexey Tsymbal:
  Dynamic Integration of Regression Models. 164-173
  
• Luca Didaci, Giorgio Giacinto:
  Dynamic Classifier Selection by Adaptive k-Nearest-Neighbourhood Rule. 174-183
  

Design Methods

• Terry Windeatt:
  Spectral Measure for Multi-class Problems. 184-193
  
• David Windridge, Robin Patenall, Josef Kittler:
  The Relationship between Classifier Factorisation and Performance in Stochastic Vector Quantisation. 194-203
  
• Claudio Marrocco, Francesco Tortorella:
  A Method for Designing Cost-Sensitive ECOC. 204-213
  
• Adam Schenker, Horst Bunke, Mark Last, Abraham Kandel:
  Building Graph-Based Classifier Ensembles by Random Node Selection. 214-222
  
• Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, Divya Bhadoria, W. Philip Kegelmeyer, Steven Eschrich:
  A Comparison of Ensemble Creation Techniques. 223-232
  
• Sarunas Raudys, Masakazu Iwamura:
  Multiple Classifiers System for Reducing Influences of Atypical Observations. 233-242
  
• Rozita A. Dara, Mohamed S. Kamel:
  Sharing Training Patterns among Multiple Classifiers. 243-252
  

Performance Analysis

• Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra:
  First Experiments on Ensembles of Radial Basis Functions. 253-262
  
• Giorgio Valentini:
  Random Aggregated and Bagged Ensembles of SVMs: An Empirical Bias?Variance Analysis. 263-272
  
• Héla Zouari, Laurent Heutte, Yves Lecourtier, Adel M. Alimi:
  Building Diverse Classifier Outputs to Evaluate the Behavior of Combination Methods: The Case of Two Classifiers. 273-282
  
• Suju Rajan, Joydeep Ghosh:
  An Empirical Comparison of Hierarchical vs. Two-Level Approaches to Multiclass Problems. 283-292
  
• Prem Melville, Nishit Shah, Lilyana Mihalkova, Raymond J. Mooney:
  Experiments on Ensembles with Missing and Noisy Data. 293-302
  

Applications

• David Windridge, Richard Bowden:
  Induced Decision Fusion in Automated Sign Language Interpretation: Using ICA to Isolate the Underlying Components of Sign. 303-313
  
• Simon Günter, Horst Bunke:
  Ensembles of Classifiers Derived from Multiple Prototypes and Their Application to Handwriting Recognition. 314-323
  
• Luigi P. Cordella, Alessandro Limongiello, Carlo Sansone:
  Network Intrusion Detection by a Multi-stage Classification System. 324-333
  
• Vladimir Svetnik, Andy Liaw, Christopher Tong, Ting Wang:
  Application of Breiman's Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules. 334-343
  
• Xiaogang Wang, Xiaoou Tang:
  Experimental Study on Multiple LDA Classifier Combination for High Dimensional Data Classification. 344-353
  
• Josef Kittler, Mohammad Sadeghi:
  Physics-Based Decorrelation of Image Data for Decision Level Fusion in Face Verification. 354-363
  
• Gian Luca Marcialis, Fabio Roli:
  High Security Fingerprint Verification by Perceptron-Based Fusion of Multiple Matchers. 364-373
  
• Fuad Rahman, Yuliya Tarnikova, Aman Kumar, Hassan Alam:
  Second Guessing a Commercial 'Black Box' Classifier by an 'In House' Classifier: Serial Classifier Combination in a Speech Recognition Application. 374-383
  

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