• 2nd CfP: 12th Symposium on Conformal and Probabilistic Prediction with

    From Harris Papadopoulos@21:1/5 to All on Thu Mar 9 15:00:09 2023
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    *** Call for Papers ***

    The 12th Symposium on Conformal and Probabilistic Prediction with
    Applications (COPA 2023)

    September 13-15, 2023, Miramare Beach Hotel, Limassol, Cyprus

    https://copa-conference.com/


    THEME

    The 12th Symposium on Conformal and Probabilistic Prediction with
    Applications (COPA 2023) will be held from the 13th to the 15th of
    September 2023, at the Miramare Beach Hotel 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    Submissions are invited on original and previously unpublished research concerning all aspects of conformal and probabilistic prediction.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 framework that
    allows making valid predictions under relatively weak statistical
    assumptions. CP can be combined with any conventional predictor for
    producing set predictions with a guaranteed accuracy, thus allowing the
    error levels to be controlled by the user. Consequently, CP has been
    widely applied to practical real-life challenges and formed the basis
    for the development of many novel approaches and extensions.

    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, including their application to interesting problems in any field.

    AWARDS

    There will be two Alexey Chervonenkis awards for the best paper and the
    best student paper. Each awardee will receive a certificate and a
    monetary prize of €100.

    TOPICS

    The topics of the symposium include, but are not limited to:

    - Theoretical analysis of conformal prediction, including
    performance guarantees
    - Novel conformity measures
    - Conformal change-point detection
    - Conformal anomaly detection
    - Conformal martingale testing
    - Conformal multi-label classification and multi-target regression
    - Venn prediction and other methods of multiprobability prediction
    - Conformal predictive distributions
    - Probabilistic prediction
    - On-line compression modelling
    - Algorithmic information theory
    - Adoption of conformal prediction to new settings
    - Implementations of conformal prediction frameworks and algorithms
    - Conformal prediction for explainable machine learning and
    Fairness, Accountability and Transparency (FAT)
    - Applications of conformal prediction in various fields, including
    bioinformatics, drug discovery, biomedicine, natural language
    processing, transportation, robotics and information security

    IMPORTANT DATES

    - Abstract Submission Deadline: March 17th, 2023
    - Paper Submission Deadline: March 24th, 2023
    - Author Notifications: May 8th, 2023
    - Camera-ready Submission Deadline: May 31st, 2023
    - Symposium Dates: September 13th - 15th, 2023

    SUBMISSIONS

    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 at:

    https://ctan.org/tex-archive/macros/latex/contrib/jmlr

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

    https://easychair.org/conferences/?conf=copa2023

    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.

    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).

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