CLD 2019 : The workshop on Classifier Learning from Difficult Data

  in Conferences   Posted on January 26, 2019

Conference Information

Submission Deadline Friday 15 Feb 2019
Conference & Submission Link
Conference Dates Jun 12, 2019 - Jun 14, 2019
Conference Address Faro, Portugal
Proceedings indexed by
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Call for Papers

Nowadays many practical decision task require to build models on the basis of data which included serious difficulties, as imbalanced class distributions, high number of classes, high-dimensional feature, small or extremely high number of learning examples, limited access to ground truth, data incompleteness, or data in motion, to enumerate only a few. Such characteristics may strongly deteriorate the final model performances. Therefore, the proposition of the new learning methods which can combat the mentioned above difficulties should be the focus of intense research. The main aim of this workshop is to discuss the problems of data difficulties, to identify new issues, and to shape future directions for research.

Topics of interest

Learning from imbalanced data

learning from data streams, including concept drift management

learning with limited ground truth access

learning from high dimensional data

learning with a high number of classes

learning from massive data, including instance and prototype selection

learning on the basis of limited data sets, including one-shot learning

learning from incomplete data

case studies and real-world applications

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