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Technical program

Program Schedule

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

Sessions Articles

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

Organized by

LAMDA Group,
National Key Laboratory for Novel Software Technology
Nanjing University (China)

Center for Vision, Speech and Signal Processing
University of Surrey (UK)

Dept. of Electrical and Electronic Engineering
University of Cagliari (Italy)

Sponsored by

Endorsed by

National Science Foundation of China

IEEE Computer Society - Nanjing Chapter

IEEE Computer Society
Nanjing Chapter

The International Association for Pattern Recognition