Call for papers:

IEEE-IJCNN 2020: special session on "Theory and Applications for Partially Labeled Data Learning"

IEEE World Congress on Computational Intelligence WCCI 2020 , Glasgow, Scotland (UK), July 19 - 24, 2020


Theory and Applications for Partially Labeled Data Learning


  • Xiaolin Huang, Associate Professor, Institute of Image Processing and Pattern Recognition, Dept. of Automation, Shanghai Jiao Tong University, China,

Objective of the session:

Despite the recent advances in deep machine learning models, there is still a huge gap between machine and human learning processes. Humans can learn from small number of instances and furthermore are able to seamlessly leverage and integrate data from different domains, whereas machines can hardly match this ability even by learning from big data. In addition, understanding, trusting, explaining the rationale behind deep models' decisions are still in their infancy. Recent years have witnessed the development of models to imitate human-like learning paradigm. In particular domain adaptation, transfer learning, zero-shot, one-shot or few-shot learning, incremental learning, active learning, multi-task and multi-view learning are examples of such models. One can anticipate that the future methodologies should be much more flexible for learning in many application domains including biomedical signal and medical image analysis, image/video classification, localization and segmentation, information retrieval and complex systems among others. Therefore, the main objective of the session is to discuss the recent rise of new research questions and learning strategies for the following problems using both shallow and deep models. The topics of interest include but not limited to:

  • Deep and shallow models
  • Neural Networks/ Kernel models
  • Explainable deep models
  • Transfer learning
  • Domain adaptation
  • Zero /One / Few-shot learning
  • Feature learning / Representation learning
  • Supervised / Semi-supervised / Unsupervised learning
  • Multi-task learning
  • Multi-view learning
  • Multi-label learning
  • Learning from heterogeneous data

Important Dates:

  • Deadline of Full Paper Submission: January 30, 2020
  • Notification of Paper Acceptance: March 15, 2020
  • IEEE WCCI 2020, Glasgow, Scotland, UK : July 19-24, 2020

Submission Guidelines:

The special session will be held at International Joint Conference on Neural Networks (, which this year is a part of IEEE World Congress on Computational Intelligence, in Glasgow, (UK), 19-24th July 2020. All papers should be prepared according to the IJCNN authors guidelines and should be submitted electronically using the conference website ( . In order to submit your paper to this special session, you have to choose our special session on the submission page. All papers accepted and presented at IEEE-IJCNN will be included in the conference proceedings published by IEEE Explore.