6. MCS 2005: Seaside, CA, USA

Future Directions

• Fabio Roli:
  Semi-supervised Multiple Classifier Systems: Background and Research Directions. 1-11
  

Boosting

• Fei Wang, Changshui Zhang, Naijiang Lu:
  Boosting GMM and Its Two Applications. 12-21
  
• Kenji Nishida, Takio Kurita:
  Boosting Soft-Margin SVM with Feature Selection for Pedestrian Detection. 22-31
  
• D. B. Redpath, K. Lebart:
  Observations on Boosting Feature Selection. 32-41
  
• Qi Tian, Jie Yu, Thomas S. Huang:
  Boosting Multiple Classifiers Constructed by Hybrid Discriminant Analysis. 42-52
  

Combination Methods

• Raymond S. Smith, Terry Windeatt:
  Decoding Rules for Error Correcting Output Code Ensembles. 53-63
  
• Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang:
  A Probability Model for Combining Ranks. 64-73
  
• Norman Poh, Samy Bengio:
  EER of Fixed and Trainable Fusion Classifiers: A Theoretical Study with Application to Biometric Authentication Tasks. 74-85
  
• Ashish Kapoor, Hyungil Ahn, Rosalind W. Picard:
  Mixture of Gaussian Processes for Combining Multiple Modalities. 86-96
  
• Eunju Kim, Jaepil Ko:
  Dynamic Classifier Integration Method. 97-107
  
• Elizabeth Tapia, Esteban Serra, José Carlos González:
  Recursive ECOC for Microarray Data Classification. 108-117
  
• Christian Thiel, Friedhelm Schwenker, Günther Palm:
  Using Dempster-Shafer Theory in MCF Systems to Reject Samples. 118-127
  
• Robin Patenall, David Windridge, Josef Kittler:
  Multiple Classifier Fusion Performance in Networked Stochastic Vector Quantisers. 128-135
  
• Pavel Paclík, Thomas Landgrebe, David M. J. Tax, Robert P. W. Duin:
  On Deriving the Second-Stage Training Set for Trainable Combiners. 136-146
  
• Sergey Tulyakov, Venu Govindaraju:
  Using Independence Assumption to Improve Multimodal Biometric Fusion. 147-155
  

Design Methods

• Hansheng Lei, Venu Govindaraju:
  Half-Against-Half Multi-class Support Vector Machines. 156-164
  
• Marina Skurichina, Robert P. W. Duin:
  Combining Feature Subsets in Feature Selection. 165-175
  
• Kyosuke Nishida, Koichiro Yamauchi, Takashi Omori:
  ACE: Adaptive Classifiers-Ensemble System for Concept-Drifting Environments. 176-185
  
• Mordechai Gal-Or, Jerrold H. May, William E. Spangler:
  Using Decision Tree Models and Diversity Measures in the Selection of Ensemble Classification Models. 186-195
  
• Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
  Ensembles of Classifiers from Spatially Disjoint Data. 196-205
  
• Thomas Landgrebe, Pavel Paclík, David M. J. Tax, Robert P. W. Duin:
  Optimising Two-Stage Recognition Systems. 206-215
  
• Lei Chen, Mohamed S. Kamel:
  Design of Multiple Classifier Systems for Time Series Data. 216-225
  
• Andreas Heß, Rinat Khoussainov, Nicholas Kushmerick:
  Ensemble Learning with Biased Classifiers: The Triskel Algorithm. 226-235
  
• Hanan Ayad, Mohamed S. Kamel:
  Cluster-Based Cumulative Ensembles. 236-245
  
• Zeki Erdem, Robi Polikar, Fikret S. Gürgen, Nejat Yumusak:
  Ensemble of SVMs for Incremental Learning. 246-256
  

Performance Analysis

• Li-ying Yang, Zheng Qin:
  Design of a New Classifier Simulator. 257-266
  
• Anand M. Narasimhamurthy:
  Evaluation of Diversity Measures for Binary Classifier Ensembles. 267-277
  
• Kaibo Duan, S. Sathiya Keerthi:
  Which Is the Best Multiclass SVM Method? An Empirical Study. 278-285
  
• Matthew Prior, Terry Windeatt:
  Over-Fitting in Ensembles of Neural Network Classifiers Within ECOC Frameworks. 286-295
  
• Gavin Brown, Jeremy L. Wyatt, Ping Sun:
  Between Two Extremes: Examining Decompositions of the Ensemble Objective Function. 296-305
  
• Rozita A. Dara, Masoud Makrehchi, Mohamed S. Kamel:
  Data Partitioning Evaluation Measures for Classifier Ensembles. 306-315
  
• Giorgio Fumera, Fabio Roli, Alessandra Serrau:
  Dynamics of Variance Reduction in Bagging and Other Techniques Based on Randomisation. 316-325
  
• Michael Muhlbaier, Apostolos Topalis, Robi Polikar:
  Ensemble Confidence Estimates Posterior Probability. 326-335
  

Applications

• Erinija Pranckeviciene, Richard Baumgartner, Ray L. Somorjai:
  Using Domain Knowledge for in the Random Subspace Method: Application: Application to the Classification of Biomedical Spectra. 336-345
  
• Peng Li, Kap Luk Chan, Sheng Fu, Shankar Muthu Krishnan:
  An Abnormal ECG Beat Detection Approach for Long-Term Monitoring of Heart Patients Based on Hybrid Kernel Machine Ensemble. 346-355
  
• Julian Fiérrez-Aguilar, Daniel Garcia-Romero, Javier Ortega-Garcia, Joaquin Gonzalez-Rodriguez:
  Speaker Verification Using Adapted User-Dependent Multilevel Fusion. 356-365
  
• Hakan Erdogan, Aytül Erçil, Hazim Kemal Ekenel, S. Y. Bilgin, Ibrahim Eden, Meltem Kirisçi, Huseyin Abut:
  Multi-modal Person Recognition for Vehicular Applications. 366-375
  
• Piero P. Bonissone, Neil H. W. Eklund, Kai Goebel:
  Using an Ensemble of Classifiers to Audit a Production Classifier. 376-386
  
• Samuel Chindaro, Konstantinos Sirlantzis, Michael C. Fairhurst:
  Analysis and Modelling of Diversity Contribution to Ensemble-Based Texture Recognition Performance. 387-396
  
• Massimo De Santo, Gennaro Percannella, Carlo Sansone, Mario Vento:
  Combining Audio-Based and Video-Based Shot Classification Systems for News Videos Segmentation. 397-406
  
• Nitesh V. Chawla, Kevin W. Bowyer:
  Designing Multiple Classifier Systems for Face Recognition. 407-416
  
• Suju Rajan, Joydeep Ghosh:
  Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data. 417-427
  

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