COPA2024: 13th Symposium on Conformal and Probabilistic Prediction with Applications Politecnico di Milano Milan, Italy, September 9-11, 2024 |
Conference website | https://copa-conference.com/ |
Submission link | https://easychair.org/conferences/?conf=copa20240 |
Submission deadline | April 22, 2024 |
The 13th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2024) will be held from September 9th to 11th, 2024, in Milan, Italy. Submissions are invited on original and previously unpublished research concerning all aspects of conformal and probabilistic prediction. The accepted papers will be published in the Proceedings of Machine Learning Research.
Conformal prediction (CP) is a modern machine and statistical learning method that allows the development of valid predictions under weak probabilistic assumptions. CP can be used to form set predictions, using any underlying point predictor, and for very general target variables, allowing the error levels to be controlled by the user. Therefore, CP has been widely used to develop robust forms of probabilistic prediction methodologies and applied to many practical real-life challenges.
Building on the work on CP, various extensions have been developed. This symposium aims 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 applicative problems in any field.
Submission Guidelines
Authors are invited to submit original, English-language research contributions or experience reports. Papers should be formatted according to JMLR (Journal of Machine Learning Research) template and style guidelines.
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.
List of Topics
- Theoretical analysis of conformal prediction, including performance guarantees and optimality results
- Applications of conformal prediction
- Novel conformity measures.
- Distribution-free uncertainty quantification
- Conformal anomaly detection.
- Conformal martingale testing and change-point detection
- Conformal prediction for non-euclidean data
- Conformal prediction for functional and high dimensional data, Multi-output conformal prediction
- Conformal prediction for temporally or spatially dependent data.
- Conformal decision theory.
- Venn prediction and other methods of multi-probability prediction.
- Distributional prediction and Conformal Predictive Distributions
- Algorithmic information theory.
- Software implementations of conformal prediction frameworks and methods.
- Conformal prediction for Explainability, Causality and Fairness, Accountability and Transparency (FAT).
The Committee is open to considering any other recent and cutting-edge development related to Conformal and Probabilistic Prediction.
Confirmed Keynote Speakers
- Prof. Johanna Ziegel (ETH Zurich, Switzerland)
- Prof. Matteo Sesia (University of Southern California, USA)
Committees
General Chair
- Prof. Simone Vantini (Politecnico di Milano, Italy).
Programme Chair
- Dr. Matteo Fontana (Royal Holloway University of London, UK).
Organizing Chairs
- Teresa Bortolotti (Politecnico di Milano, Italy)
- Dr. Khuong An Nguyen (Royal Holloway, University of London)
- Alfredo Gimenez Zapiola (Politecnico di Milano, Italy)
Publication Chairs
- Prof. Aldo Solari (Ca' Foscari University of Venice, Italy)
- Prof. Henrik Boström (KTH Royal Institute of Technology, Sweden)
- Prof. Lars Carlsson (Jönköping University, Sweden)
Publication Chairs
- Dr. Giovanni Cherubin (Microsoft Research, UK)
- Dr. Tuwe Löfström (Jönköping University, Sweden)
Administration Chairs
- Laura Guarino (Politecnico di Milano, Italy)
- Anna Rho (Politecnico di Milano, Italy)
Honorary Chairs
- Prof. Vladimir Vapnik (Facebook AI Research, Columbia University, USA).
- Prof. Alexander Gammerman (Royal Holloway University of London, UK).
- Prof. Vladimir Vovk (Royal Holloway University of London, UK).
Publication
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 230.
Venue
The conference will be held at Politecnico di Milano, Leonardo Campus in Milan, Italy.
Contact
For questions about submissions, please email Matteo.Fontana@rhul.ac.uk