<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div class="">*** Apologies for cross posting ***</div><div class=""><br class=""></div><div class="">ESANN 2015 Special Session “Feature and Kernel Learning” - CALL FOR PAPERS<span class="Apple-tab-span" style="white-space: pre;"> </span></div><div class=""><br class=""></div><div class="">European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2015). 22-24 April 2015, Bruges Belgium <a href="http://www.esann.org" class="">http://www.esann.org</a></div><div class=""><br class=""></div><div class="">Submissions are invited for next year ESANN Special Session “Feature and Kernel Learning”</div><div class=""><br class=""></div><div class="">Organizers:</div><div class=""><br class=""></div><div class="">Veronica Bolon-Canedo (University of A Coruña, Spain)</div><div class="">Michel Donini, Fabio Aiolli (University of Padova, Italy)</div><div class=""><br class=""></div><div class="">ABSTRACT:</div><div class=""><br class=""></div><div class=""><div class="">Feature selection and weighting has been an active research area in the last decades finding success in many different applications. With the advent of Big Data, the adequate identification of the relevant features has converted feature selection in an even more indispensable step. In particular, in kernel methods features are implicitly represented by means of feature mappings and kernels. It has been shown that the correct selection of a kernel is a crucial task. An erroneous selection of a kernel can lead to poor performance. Manually searching for an optimal kernel is a time-consuming and a sub-optimal choice. </div><div class="">This special session is concerned with using data to learn features and kernels automatically. Furthermore, it also aims to offer a meeting opportunity for academics and industry-related researchers, belonging to the various communities of Computational Intelligence, Machine Learning and Data Mining to discuss new areas of feature selection/learning and their application to real world problems or new challenges that need to be faced with the emerging "Big Dimensionality". </div><div class=""><br class=""></div><div class="">We invite papers on feature and kernel selection/learning. In particular, topics of interest include, but are not limited to:</div><div class=""><br class=""></div><div class="">- Incremental or online feature learning</div><div class="">- Learning features in extremely high dimensional domains</div><div class="">- Learning features on real applications</div><div class="">- Learning features on small sample domains</div><div class="">- Feature ranking</div><div class="">- Feature weighting</div><div class="">- Multiple kernel learning</div><div class="">- Kernel complexity</div><div class="">- Scalability and efficiency of feature and kernel learning algorithms</div><div class="">- Evaluation of feature learning</div><div class="">- Multi-task and multi-view feature learning </div><div class="">- Semi-supervised and unsupervised feature learning</div><div class=""><br class=""></div><div class="">Submitted papers will be reviewed according to the ESANN reviewing process and will be evaluated on their scientific value: originality, correctness, and writing style.</div></div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">SUBMISSION AND IMPORTANT DATES:</div><div class=""><br class=""></div><div class="">We kindly invite you to submit a paper to this special session. Each paper will undergo to a peer reviewing process for its acceptance. Paper submission should be done exclusively through the ESANN portal following the instructions provided in:</div><div class=""><a href="http://www.elen.ucl.ac.be/esann/index.php?pg=submission" class="">http://www.elen.ucl.ac.be/esann/index.php?pg=submission</a></div><div class=""><br class=""></div><div class="">Paper submission deadline: 21 November 2014</div><div class="">Notification of acceptance: 31 January 2015</div><div class="">ESANN 2015 conference: 22-24 April 2015</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">More information about the Conference Program, accomodation facilities and registration fees is available on the ESANN website <a href="http://www.esann.org" class="">http://www.esann.org</a></div><div class=""><br class=""></div><div class=""><br class=""></div><br class=""><div apple-content-edited="true" class=""><div style="orphans: 2; text-align: -webkit-auto; widows: 2; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div class=""><font color="#929292" class="">Verónica Bolón Canedo, Ph.D.</font></div><div class=""><font color="#929292" class="">LIDIA group</font></div><div class=""><font color="#929292" class="">Department of Computer Science</font></div><div class=""><font color="#929292" class="">Faculty of Informatics</font></div><div class=""><font color="#929292" class="">Universidade da Coruña</font></div><div class=""><font color="#929292" class=""><br class=""></font></div><div class=""><font color="#929292" class="">Campus de Elviña, s/n</font></div><div class=""><font color="#929292" class="">15071 - A Coruña, Spain</font></div><div class=""><font color="#929292" class=""><br class=""></font></div><div class=""><font color="#929292" class="">Phone: +34 981 167150 Ext. 1305</font></div><div class=""><font color="#929292" class="">Fax: +34 981 167160</font></div><div class=""><font color="#929292" class="">e-mail: <a href="mailto:veronica.bolon@udc.es" class="">veronica.bolon@udc.es</a></font></div><div class=""><font color="#929292" class=""><a href="http://www.lidiagroup.org/veronica-bolon.html" class="">http://www.lidiagroup.org/veronica-bolon.html</a></font></div></div></div></body></html>