AMAI 2013 - AMAI Special Issue on Conformal Prediction and its Applications

Special Issue on Conformal Prediction and its Applications
Annals of Mathematics and Artificial Intelligence
(http://www.springer.com/computer/ai/journal/10472)
Topic description:
Quantifying the uncertainty of the predictions produced by classification and regression techniques is an important problem in the field of Machine Learning. Conformal Prediction is a recently developed framework for complementing the predictions of Machine Learning algorithms with reliable measures of confidence. The methods developed based on this framework produce well-calibrated confidence measures for individual examples without assuming anything more than that the data are generated independently by the same probability distribution (i.i.d.). Since its development the framework has been combined with many popular techniques, such as Support Vector Machines, k-Nearest Neighbours, Neural Networks, Ridge Regression etc., and has been successfully applied to many challenging real world problems, such as the early detection of ovarian cancer, the classification of leukaemia subtypes, the diagnosis of acute abdominal pain, the assessment of stroke risk, the recognition of hypoxia in electroencephalograms (EEGs), the prediction of plant promoters, the prediction of network traffic demand, the estimation of effort for software projects and the backcalculation of non-linear pavement layer moduli. The framework has also been extended to additional problem settings such as semi-supervised learning, anomaly detection, feature selection, outlier detection, change detection in streams and active learning.
The main focus of this special issue is on recent developments and extensions of the Conformal Prediction framework and on its application to interesting problems where the provision of confidence information is valuable. We welcome authors to submit their original research articles, as well as comprehensive reviews on this new topic. Besides the dissemination of the latest results and findings on new theoretical advances and applications of the Conformal Prediction framework it is expected that this special issue will deliver new ideas and identify directions for future research.
Paper submission and review:
Manuscripts must follow the AMAI guidelines for submission and have to be accompanied by abstracts. Details regarding the submission format and the on-line submission site can be found at http://www.editorialmanager.com/amai/. All manuscripts for this Special Issue should be submitted through this online system by selecting the Submission Type "S70: Conformal Prediction and its Applications".
All submitted manuscripts must be of high quality and will be evaluated based on their originality, presentation, relevance and contribution to the field, as well as their suitability to the special issue and their overall quality. The refereeing will be at the same level as in any of the major journal publications in the area. Manuscripts must be written in excellent English and describe original research which has not been published nor is currently under review by other journals or conferences. Previously published conference/workshop papers should be clearly identified by the authors (at the submission stage) and an explanation should be provided how such papers have been extended to be considered for this special issue. Guest editors will make an initial determination of the suitability and scope of all submissions. Manuscripts that either lack originality, clarity in presentation or fall outside the scope of the special issue will not be sent for review and the authors will be promptly informed in such cases.
Important dates:
Paper submission deadline: December 15, 2012
Notification of initial decisions: March 15, 2013
Revised submission deadline: May 31, 2013
Notification of final decisions: July 31, 2013
Final papers: August 31, 2013
About Annals of Mathematics and Artificial Intelligence:
Annals of Mathematics and Artificial Intelligence (AMAI) is devoted to reporting significant contributions on the interaction of mathematical and computational techniques reflecting the evolving discipline of artificial intelligence. Annals of Mathematics and Artificial Intelligence publishes edited volumes of original manuscripts, survey articles, monographs and well refereed conference proceedings of the highest caliber within this increasingly important field. All papers will be subject to the peer reviewing process with at least two referees per paper.
Guest editors:
Harris Papadopoulos
Frederick University, Cyprus
harris.papadopoulos-AT-gmail.com
Alex Gammerman
Royal Holloway, University of London
A.Gammerman-AT-cs.rhul.ac.uk
Vladimir Vovk
Royal Holloway, University of London
V.Vovk-AT-rhul.ac.uk