Multi-Label Learning

Current Trends and Open Challenges

ECML PKDD 2022 19 September, Grenoble

Call for Papers


This workshop aims to bring researchers and practitioners that work on different aspects of multi-label learning into a fruitful discussion about the state-of-the-art, remaining open problems, and new promising research directions. The workshop welcomes both theoretical multi-label learning papers, as well as papers discussing real-world applications involving multi-label data. We are particularly interested in submissions of papers at the intersection of human-centered trustworthy machine learning aspects (e.g., interpretability, explainability, bias, fairness, safety, active learning) and multi-label learning, as well as papers discussing persistent challenges in multi-label data (e.g., data streams, extreme classification, class imbalance, missing labels, noisy labels, real-world industrial aspects). The workshop is open to papers dealing with any type of data modality (e.g., textual, visual, tabular). The best paper of the workshop will be awarded with a free ECML PKDD 2022 registration.


Topics

The topics of the workshop include, but are not limited to:
  • Methods for multi-label classification and ranking
  • Statistical and semantic analysis of multi-label data
  • Evaluation measures and strategies for multi-label data
  • Learning label structure and relationships
  • Embeddings and representations of multi-label data
  • FAIR multi-label data
  • Explainable multi-label learning
  • Trustworthy multi-label learning
  • Extreme multi-label classification
  • Deep multi-label learning
  • Dealing with class imbalance
  • Learning from partially labeled data
  • Weak multi-label learning
  • Zero-shot and few shot multi-label learning
  • Semi-supervised learning from multi-label data
  • Active learning from multi-label data
  • Dimensionality reduction (feature selection) of multi-label data
  • Hierarchical multi-label classification and learning
  • Learning from streams of multi-label data
  • Applications in a variety of domains, including life sciences, medicine, engineering, and multimedia

Form

The workshop will have a half-day duration, featuring invited talks from world-class experts, oral presentations of all accepted papers, a poster session for additional discussion of each accepted paper among workshop participants, and finally a session dedicated to openly discussing challenges and opportunities in multi-label learning. The workshop will take place as a hybrid event. However, as interactions and discussions are much easier and more fruitful face-to-face, we encourage especially speakers, but also participants, to join us physically in beautiful Grenoble.

Important Dates