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COPA 2023 : 12th Symposium on Conformal and Probabilistic Prediction with Applications


When Sep 13, 2023 - Sep 15, 2023
Where Limassol, Cyprus
Abstract Registration Due Mar 31, 2023
Submission Deadline Apr 7, 2023
Notification Due May 8, 2023
Final Version Due May 31, 2023
Categories    conformal martingale testing   probabilistic prediction   venn prediction   multiprobability prediction

Call For Papers

The 12th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023) will be held from September 13th to 15th, 2023, in Limassol, Cyprus. Submissions are invited on original and previously unpublished research concerning all aspects of conformal and probabilistic prediction. The symposium proceedings will be published in the Proceedings of Machine Learning Research.

Conformal prediction (CP) is a modern machine learning method that allows to make valid predictions under relatively weak statistical assumptions. CP can be used to form set predictions, using any underlying point predictor, allowing the error levels to be controlled by the user. Therefore, CPs have been widely applied to many practical real life challenges.

Building on the work on CP, various extensions have been developed recently. The aim of this symposium is to serve as a forum for the presentation of new and ongoing work and the exchange of ideas between researchers on any aspect of conformal and probabilistic prediction and their applications to interesting problems in any field.

Topics of the symposium include, but are not limited to:

Theoretical analysis of conformal prediction, including performance guarantees
Applications of conformal prediction in various fields, including bioinformatics, drug discovery, medicine, and information security
Novel conformity measures
Conformal change-point detection
Conformal anomaly detection
Conformal martingale testing
Venn prediction and other methods of multiprobability prediction
Conformal predictive distributions
Probabilistic prediction
On-line compression modelling
Prediction in: Machine learning, Pattern recognition, Data mining, Transfer learning
Algorithmic information theory
Implementations of conformal prediction frameworks and algorithms
Conformal prediction for explainable machine learning and Fairness, Accountability and Transparency (FAT)
Data visualization
Big data applications

Authors are invited to submit original, English-language research contributions or experience reports. Papers should be no longer than 20 pages formatted according to the well-known JMLR (Journal of Machine Learning Research) style. The LaTeX package for the style is available here.

All aspects of the submission and notification process will be handled online via the EasyChair Conference System at:

Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the symposium to present the work.

Submitted papers will be refereed for quality, correctness, originality, and relevance. Notification and reviews will be communicated via email. All accepted papers will be presented at the Symposium and published in the PMLR (Proceedings of Machine Learning Research), Volume 204.

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