Author: Alejandro Moreo;
Binary quantification and dataset shift: an experimental investigation
Regularization-Based Methods for Ordinal Quantification
Report on the 3rd International Workshop on Learning to Quantify (LQ 2023)
Proceedings of the 3rd International Workshop on Learning to Quantify (LQ 2023)
The 3rd International Workshop on Learning to Quantify (LQ 2023 – https: //lq-2023.github.io/) was held in Torino, IT, on September 18, 2023, as a satellite workshop of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2023). While the 1st edition of the workshop (LQ 2021 – https://cikmlq2021. github.io/) had to be an entirely online event, LQ 2023 (like the 2nd edi- tion LQ 2022 – https://lq-2023.github.io/) was a hybrid event, with presentations given in-presence, and both in-presence attendees and remote attendees. The workshop was the second part (Sep 18 afternoon) of a full-day event, whose first part (Sep 18 morning) consisted of a tutorial on Learning to Quantify presented by Alejandro Moreo and Fabrizio Sebastiani. The LQ 2023 workshop consisted of the presentations of seven contributed papers, and a final collective discussion on the open problems of learning to quantify and on future initiatives.
The present volume contains five of the seven contributed papers that were accepted for presentation at the workshop (the authors of the other two papers decided not to have their paper included in the proceedings). Each contributed paper was submitted as a response to the call for papers, was reviewed by at least three members of the international program commit- tee, and was revised by the authors so as to take into account the feedback provided by the reviewers.