Call for papers

Special Session on “MACHINE LEARNING FOR PARTIALLY LABELED DATA”

To be held at the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2022)

https://ipmu2022.disco.unimib.it/submission/

Milan (Italy), July 11-15, 2022

Session topic and goal

This session aims to target Machine Learning techniques for dealing with incompletely labeled data. Typically, the most effective Machine Learning systems are those based on training data that are fully labeled. However, obtaining fully labeled data can be an infeasible task in many fields due to the involved costs or required resources. As a result, recently, increasing interest has been devoted to the development of techniques capable of dealing with incompletely labeled data. Several types of learning problems have been considered, including semi-supervised learning but also more general forms of weak supervision, and various techniques for solving these problems have been explored over the years, also in terms of novel conceptual frameworks that aim to shed a light on this topic. Nevertheless, there are still many open problems.

This special session is intended to serve as a common space for researchers in this field to share their latest findings on incompletely labeled data, including the development of practical algorithms to address different tasks based on such kind of data, as well as the conceptual foundations of this area.

The topics of interest include (but are not limited to):

• Semi-supervised learning 

• Weak label learning

• Active learning

• Partial label learning

• Multi-label learning 

• Transfer learning

• Few-shot learning

• Zero-shot learning 

• Contrastive learning

Dates

Paper submission: Friday, 14 January 2022 EXTENDED: Friday, 18 February 2022

Notification of Acceptance: Tuesday, 1 March 2022 EXTENDED: Friday, 1 April 2022

Conference: July 11-15, 2022

Organizers

Any questions or remarks can be addressed to:

Andrea Campagner (a.campagner@campus.unimib.it), University of Milano-Bicocca (Italy) 

Nahuel Costa Cortez (costanahuel@uniovi.es), University of Oviedo (Spain)

Luciano Sanchez Ramos (luciano@uniovi.es), University of Oviedo (Spain)