Important Dates:
Paper submission: April 29, 2012 May 15, 2012
Notification of acceptance/rejection: May 26, 2012 June 10, 2012
Camera-ready submission: June 4, 2012 June 15, 2012
Early registration: June 04, 2012 June 25th, 2012
Workshop dates: To be announced

Honorary Chairs
Vladimir Vapnik
NEC, USA and Royal Holloway, University of London, UK

Alexei Chervonenkis
Russian Academy of Sciences, Russia and Royal Holloway, University of London, UK

Program Chairs
Harris Papadopoulos
Frederick University, Cyprus
h.papadopoulos@frederick.ac.cy

Alex Gammerman
Royal Holloway, University of London, UK
alex@cs.rhul.ac.uk

Vladimir Vovk
Royal Holloway, University of London, UK
vovk@cs.rhul.ac.uk

Workshop Program Committee (not complete)

• Vineeth Balasubramanian, Arizona State University, USA
• Anthony Bellotti, Imperial College London, UK
• David R. Hardoon, SAS, Singapore
• Shen-Shyang Ho, Nanyang Technological University, Singapore
• Zakria Hussain, University College London, UK
• Yuri Kalnishkan, Royal Holloway, University of London, UK
• Matjaz Kukar, University of Ljubljana, Slovenia
• Antonis Lambrou, Royal Holloway, University of London, UK
• Rikard Laxhammar, University of Skovde, Sweden
• Yang Li, Chinese Academy of Sciences, China
• Zhiyuan Luo, Royal Holloway, University of London, UK
• Andrea Murari, Consorzio RFX, Italy
• Ilia Nouretdinov, Royal Holloway, University of London, UK
• Savvas Pericleous, Frederick University, Cyprus
• David Surkov, Egham Capital, UK
• Jesus Vega, Asociacion EURATOM/CIEMAT para Fusion, Spain
• Fan Yang, Xiamen University, China
• Mohamed Hebiri, Université de Marne-la-Vallée, France

Workshop Aim: 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 feature selection, outlier detection, change detection in streams and active learning. The aim of this workshop 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 Prediction and its applications.

The workshop welcomes submissions introducing further developments and extensions of the Conformal Prediction framework and describing its application to interesting problems of any field.

Submission:
Authors are invited to submit original, English-language research contributions or experience reports. Papers should be no longer than 10 pages formatted according to the well-known LNCS Springer style. Papers should be submitted either in a doc or in a pdf form to h.papadopoulos@frederick.ac.cy

Publication:
Submitted papers will be refereed for quality, correctness, originality, and relevance. Notification and reviews will be communicated via email. Accepted papers will be presented at the workshop and published in the Proceedings of the main event (by Springer). They will also be considered for potential publication in the Special Issues of the Conference.

Registration fees and benefits for the workshops' participants are exactly identical with the ones of the main AIAI 2012 event.