Welcome

Quantification and classification are two supervised learning tasks that, in real applications, are often hampered by changes in data distributions, i.e., by dataset shift. The two tasks differ in what trained models predict: while a classifier predicts the class label of each individual data point, a quantifier predicts the prevalence (i.e., relative frequency) of each class in a set of unlabelled data points. Both classifiers and quantifiers can suffer if dataset shift is at play, at least as long as they are not designed to handle the current type of shift robustly. Research has shown that a quantifier robust to dataset shift can facilitate robust classification, and a classifier robust to dataset shift can facilitate robust quantification.

QCDS 2026, a workshop co-located with the ECML/PKDD 2026 conference, aims to engage the diverse expertise of the ECML/PKDD community; as dataset shift remains a fundamental challenge in real-world deployments, understanding the interplay between classification and quantification is more critical than ever. This workshop provides a collaborative forum for researchers and practitioners to bridge the gap between these two vital fields, to share breakthroughs in machine learning methods robust to dataset shift, and to explore emerging applications.

QCDS 2026 is a follow-up of the Learning to Quantify (LQ) workshop series; while the LQ workshops concentrated exclusively on quantification under dataset shift, QCDS 2026 has a broadened scope, and also encompasses classification under dataset shift and how, when dataset shift is at play, quantification and classification may bring mutual benefit.

QCDS 2026 is supported by project “Future Artificial Intelligence Research” (FAIR) and project “Strengthening the Italian RI for Social Mining and Big Data Analytics” (SoBigData.it), both funded by the European Union under the NextGenerationEU funding scheme (CUP B53D22000980006 and CUP B53C22001760006, respectively) and by the Agency for Science, Business Competitiveness, and Innovation of the Principality of Asturias in Spain (SEKUENS) through the project GRU-GIC-24-018.

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Call for papers for the QCDS 2026 Workshop

We seek papers on any of the following topics (where QCDS stands for "Quantification AND/OR Classification under Dataset Shift"), which will form the main themes of the QCDS 2026 workshop:

  • Binary, multiclass, multilabel, and ordinal QCDS
  • Semi-supervised / transductive QCDS
  • Multi-instance learning / learning for set-structured data
  • Deep learning for QCDS
  • Characterizations of dataset shift, and their impact on QCDS
  • Detecting and measuring (different types of) dataset shift
  • Evaluation measures and protocols for QCDS
  • Improving classification under dataset shift via quantification
  • Classifier calibration under dataset shift
  • New datasets and applications for evaluating QCDS

and other topics of relevance to QCDS. Two categories of papers are of interest:

  • papers reporting original, unpublished research;
  • papers {published in 2026 / currently under submission / accepted in 2026} at other {workshops / conferences / journals}, provided this double submission does not violate the rules of these {workshops / conferences / journals}.
Submission

Papers should be submitted (specifying which of the two above categories they belong to) via EasyChair.

Papers should be formatted according to Springer’s LNCS template, and should be up to 16 pages (including references) in length; however, this is just the upper bound, and contributions of any length up to this bound will be considered.

** Important information **

By submitting a paper the authors acknowledge that, in case of acceptance, one of them will register (according to the rules set by the ECML/PKDD 2026 organizers) and present the paper in presence at the workshop.

About the proceedings

The proceedings of the workshop will not be formally published, so as to allow authors to resubmit their work to other venues and so as to avoid putting the papers behind behind paywalls. Informal proceedings will be published on the workshop website; however, for each accepted paper, it will be left at the discretion of the authors to decide whether to contribute their paper or not to these proceedings.

Important dates (all deadlines are 23:59 AoE)
  • Paper submission deadline: June 5, 2026
  • A/R notification deadline: June 29, 2026
  • Final copy submission deadline: July 10, 2026
  • Workshop: September 7, 2026

Organizers

Mirko Bunse

Mirko Bunse

Artificial Intelligence Group, TU Dortmund University, Germany

Pablo González

Pablo González

Artificial Intelligence Center, University of Oviedo, Spain

Eyke Hüllermeier

Eyke Hüllermeier

Institute of Informatics at LMU Munich, Germany

Alejandro Moreo

Alejandro Moreo

Istituto di Scienza e Tecnologie dell’Informazione, Consiglio Nazionale delle Ricerche, Pisa, Italy

Fabrizio Sebastiani

Fabrizio Sebastiani

Istituto di Scienza e Tecnologie dell’Informazione, Consiglio Nazionale delle Ricerche, Pisa, Italy

Program Committee
  • Gustavo Batista, University of New South Wales, AU
  • Clemens Damke, Ludwig Maximilian University of Munich, DE
  • Juan José del Coz, University of Oviedo, ES
  • Zahra Donyavi, University of New South Wales, AU
  • Andrea Esuli, Consiglio Nazionale delle Ricerche, IT
  • Cèsar Ferri, Universitat Politècnica de València, ES
  • Peter Flach, University of Bristol, UK
  • Devin Guillory, UC Berkeley, US
  • Barbara Hammer, University of Bielefeld, DE
  • Rafael Izbicki, Federal University of São Carlos, BR
  • Mira Jürgens, Gent University, BE
  • André Maletzke, Universidade Estadual do Oeste do Paraná, BR
  • Olaya Pérez-Mon, University of Oviedo, ES
  • Teodora Popordanovska, KU Leuven, BE
  • Marco Saerens, Catholic University of Louvain, BE
  • Tobias Schumacher, University of Mannheim, DE
  • Dirk Tasche, North-West University, SA
  • Lorenzo Volpi, Consiglio Nazionale delle Ricerche, IT
  • Willem Waegeman, Ghent University, BE

Program

The detailed program of the workshop, which will include the full list of papers to be presented, will be published in early July.

Special Issue of the Data Mining and Knowledge Discovery journal on QCDS

An agreement has been reached with the Data Mining and Knowledge Discovery journal (Springer) for a special issue of the journal that will consist of revised versions of selected papers presented at the QCDS 2026 workshop. More details (e.g., important dates) to be announced later.