Workshop on Learning in the Presence of Class Imbalance and Concept Drift



The workshop proceeding can be downloaded from here.


An example about including a figure.

The workshop will be held on 20th of August. There will be two invited talks and presentations/discussions from eight accepted papers. The agenda of the day is:

  • Workshop Begins
    • 08:50-09:00: Opening, Xin Yao
  • Keynote 1
    • 09:00-10:00: Joao Gama, University of Porto, Portugal
  • Coffee break (10:00-10:30 strict)
  • Morning Sessions (10:30-12:30) chaired by Romero Morais
    • 10:30-11:00: Linear Classifier Design for Heteroscedastic LDA under Class Imbalance, by Kojo Sarfo Gyamfi, James Brusey, Andrew Hunt and Elena Gaura
    • 11:00-11:30: Under-Sampling the Minority Class to Improve the Performance of Over-Sampling Algorithms in Imbalanced Data Sets, by Romero Morais and Germano Vasconcelos
    • 11:30-12:00: Predicting Risk Level of Executables: an Application of Online Learning, by Huynh Ngoc Anh, Wee Keong Ng and Kanishka Ariyapala
    • 12:00-12:30: Co-training semi-supervised learning for single-target regression in data streams using Random AMRules, by Ricardo Sousa and João Gama
  • Lunch break (12:30-14:30)
  • Keynote 2
    • 14:30-15:30: Dacheng Tao, University of Sydney, Australia
  • Afternoon Session (15:30-17:30) chaired by Ruolin Jia
    • 15:30-16:00: An Oversampling Method based on Shapelet Extraction for Imbalanced Time Series Classification, by Qiu-Yan Yan, Fanrong Meng and Qifa Sun
    • 16:00-16:30: Coffee break
    • 16:30-17:00: Predicting Concept Drift Severity, by Ruolin Jia, Yun Sing Koh and Gill Dobbie
    • 17:00-17:30: On Solving the Class Imbalance Problem for Clinical Decision Improvement Using Heart Sound Signals, by Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh and Arpan Pal