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Label noise at ESANN 2014 : Special session on Label noise in classification at ESANN 2014 | |||||||||||||
Link: https://www.elen.ucl.ac.be/esann/index.php?pg=specsess#Label%20noise%20in%20classification | |||||||||||||
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Call For Papers | |||||||||||||
Call for papers: special session on "Label noise in classification" at ESANN 2014
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014). 23-25 April 2014, Bruges, Belgium - http://www.esann.org DESCRIPTION: In classification, it is difficult to obtain completely reliable labels. Indeed, labels are often polluted by label noise, due to e.g. insufficient information or expert mistakes. Many works have tackled the problem of learning in the presence of label noise. Filtering methods have been developed to detect and remove mislabelled instances. Also, recent approaches attempt to take label noise into account while learning, using e.g. probabilistic models of label noise or prior knowledge about the influence of label noise on specific methods. Other settings like e.g. semi-supervised learning have also been studied. This special session aims to provide a forum where researchers could discuss the most recent developments in the field of label noise. Contributions should propose new methods to deal with label noise, new applications where label noise must be taken into account, theoretical results about learning in the presence of label noise or experimental results which provide insight about existing methods. Examples of topics of interest include (but are not limited to) the following: - when are noisy labels better than no labels at all? - what makes a classifier robust to label noise? - dealing with different types of label noise (random, non-random, malicious, or adversarial) - conditions for the consistency of classification in the presence of label noise - label noise in high dimensional small sample settings - the issue of model order selection in the presence of label noise - feature selection and dimensionality reduction in the presence of label noise - label-noise aware classification algorithms in static and dynamic scenarios - learning with side information to counter label noise SUBMISSION: Prospective authors must submit their paper through the ESANN portal following the instructions provided in http://www.elen.ucl.ac.be/esann/index.php?pg=submission. Each paper will undergo a peer reviewing process for its acceptance. Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers. IMPORTANT DATES: Paper submission deadline : 29 November 2013 Notification of acceptance : 31 January 2014 The ESANN 2014 conference : 23-25 April 2014 SPECIAL SESSION ORGANISERS: Dr. Benoît Frénay Université catholique de Louvain, Belgium E-mail: benoit.frenay@uclouvain.be Website: http://bfrenay.wordpress.com Phone: +32 10 478133 Dr. Ata Kaban University of Birmingham, United Kingdom E-mail: A.Kaban@cs.bham.ac.uk Website: http://www.cs.bham.ac.uk/~axk Phone: +44 121 41 42792 |
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