May 15
07:30	Bus pickup
08:30 - 08:40	Opening
08:40 - 09:40	Invited Talk: Prof. Bin Yu
09:40 - 09:55	Coffee break
09:55 - 12:00	Session 1: Diversity and Selective Ensemble
12:00 - 12:30	Lunch
12:30 - 18:30	Excursion
18:30 - 21:00	Banquet
May 16
07:30	Bus pickup
08:30 - 09:30	Invited Talk: Prof. Marcello Pelillo
09:30 - 09:45	Coffee break
09:45 - 11:50	Session 2: Class-Imbalance Learning
11:50 - 12:50	Lunch
12:50 - 14:55	Session 3: Feature Processing
14:55 - 15:10	Coffee break
15:10 - 17:40	Session 4: Classifier Ensemble
17:40	Dinner
May 17
07:30	Bus pickup
08:30 - 09:30	Invited Talk: Prof. Xin Yao
09:30 - 09:45	Coffee break
09:45 - 11:50	Session 5: Multi-Instance and Part-Based Learning
11:50 - 12:50	Lunch
12:50 - 14:05	Session 6: Clustering Ensemble
14:05 - 14:15	Coffee break
14:15 - 16:20	Session 7: Applications
16:20 - 16:25	Closing
16:25	Lab visit, campus tour and leave

Session 1: Diversity and Selective Ensemble
• Diversity in Classifier Ensembles: Fertile Concept or Dead End?
  Luca Didaci, Giorgio Fumera, and Fabio Roli
• Can Diversity amongst Learners Improve Online Object Tracking?
  Georg Nebehay, Walter Chibamu, Peter R. Lewis, Arjun Chandra,? Roman Pflugfelder, and Xin Yao
• Selective Ensemble of Classifier Chains
  Nan Li, and Zhi-Hua Zhou
• ECOC Matrix Pruning Using Accuracy Information
  Cemre Zor, Terry Windeatt, and Josef Kittler
• Selective Clustering Ensemble Based on Covariance
  Xuyao Lu, Yan Yang, and Hongjun Wang

Session 2: Class-Imbalance Learning
• Random Oracle Ensembles for Imbalanced Data
  Juan J. Rodríguez, José-Francisco Díez-Pastor, and César García-Osorio
• Ensembles of Optimum-Path Forest Classifiers Using Input Data Manipulation and Undersampling
  Moacir P. Ponti Jr., and Isadora Rossi
• Similarity Weighted Ensembles for Relocating Models of Rare Events
  Claire D'Este, and Ashfaqur Rahman
• Adaptive Ensemble Selection for Face Re-identification under Class Imbalance
  Paulo Radtke, Eric Granger, Robert Sabourin, and Dmitry Gorodnichy
• Cascaded Reduction and Growing of Result Sets for Combining Object Detectors
  Uwe Knauer and Udo Seiffert

Session 3: Feature Processing
• Dimensionality Reduction Using Stacked Kernel Discriminant Analysis for Multi-label Classification
  Muhammad Atif Tahir, Ahmed Bouridane, and Josef Kittler
• Stable L2-Regularized Ensemble Feature Weighting
  Yun Li, Shasha Huang, Songcan Chen, and Jennie Si
• Ensemble of Feature Chains for Anomaly Detection
  Lena Tenenboim-Chekina, Lior Rokach, and Bracha Shapira
• A New Feature Fusion Approach Based on LBP and Sparse Representation and Its Application to Face Recognition
  He-Feng Yin and Xiao-Jun Wu
• Feature Level Multiple Model Fusion Using Multilinear Subspace Analysis with Incomplete Training Set and Its Application to Face Image Analysis
  Zhen-Hua Feng, Josef Kittler, William Christmas, and Xiao-Jun Wu

Session 4: Classifier Ensemble
• Towards a Framework for Designing Full Model Selection and Optimization Systems
  Quan Sun, Bernhard Pfahringer, and Michael Mayo
• Coding Theory Tools for Improving Recognition Performance in ECOC Systems
  Claudio Marrocco, Paolo Simeone, and Francesco Tortorella
• A Directed Inference Approach towards Multi-class Multi-model Fusion
  Tianbao Yang, Lei Wu, and Piero P. Bonissone
• Randomized Bayesian Network Classifiers
  Qing Wang and Ping Li
• Self-Organizing Neural Grove and Its Application to Incremental Learning
  Hirotaka Inoue
• A Novel Pattern Rejection Criterion Based on Multiple Classifiers
  Wei-Na Wang, Xu-Yao Zhang, and Ching Y. Suen

Session 5: Multi-Instance and Part-Based Learning
• The Link between Multiple-Instance Learning and Learning from Only Positive and Unlabelled Examples
  Yan Li, David M.J. Tax, Robert P.W. Duin, and Marco Loog
• Combining Instance Information to Classify Bags
  Veronika Cheplygina, David M.J. Tax, and Marco Loog
• Transfer Learning with Part-Based Ensembles
  Shiliang Sun, Zhijie Xu, and Mo Yang
• Improving Simple Collaborative Filtering Models Using Ensemble Methods
  Ariel Bar, Lior Rokach, Guy Shani, Bracha Shapira, and Alon Schclar
• Single Classifier Based Multiple Classifications
  Albert Hung-Ren Ko and Robert Sabourin

Session 6: Clustering Ensemble
• Soft-Voting Clustering Ensemble
  Haishen Wang, Yan Yang, Hongjun Wang, and Dahai Chen
• Semi-Supervised Clustering Ensemble for Web Video Categirization
  Amjad Mahmood, Tianrui Li, Yan Yang, Hongjun Wang, and? Mehtab Afzal
• A New Perspective of Support Vector Clustering with Boundary Patterns
  Yuan Ping, Huina Li, Yong Zhang, and Zhili Zhang

Session 7: Applications
• Multi-View Multi-Class Classification for Identification of Pathogenic Bacterial Strains
  Evgeni Tsivtsivadze, Tom Heskes, and Armand Paauw
• MRF-Based Multiple Classifier System for Hyperspectral Remote Sensing Image Classification
  Junshi Xia, Peijun Du, and Xiyan He
• Kalman Filter Based Classifier Fusion for Affective State Recognition
  Michael Glodek, Stephan Reuter, Martin Schels, Klaus Dietmayer, and Friedhelm Schwenker
• Gender Classification Using Mixture of Experts from Low Resolution Facial Images
  Yomna Safaa El-Din, Mohamed N. Moustafa, and Hani Mahdi
• Binary Decision Trees for Melanoma Diagnosis
  Yu Zhou, and Zhuoyi Song