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

last updated on Tue May 21 02:18:25 2013 by the dblp team
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