<div dir="ltr"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Apologies for cross-posting. Kindly help to distribute this<span> </span><span class="gmail-il">call</span><span> </span>to your mailing list.</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline"><span class="gmail-il">INNS</span><span> </span>BIG DATA AND DEEP LEARNING<span> </span><span class="gmail-il">2019</span></span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">SESTRI LEVANTE, GENOA, ITALY, 16-18 APRIL<span> </span><span class="gmail-il">2019</span></span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><a href="https://innsbddl2019.org/" target="_blank" style="color:rgb(17,85,204);font-size:small">HTTPS://INNSBDDL2019.ORG/</a><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">WEBSITE<span> </span></span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><a href="https://innsbddl2019.org/" target="_blank" style="color:rgb(17,85,204);font-size:small">https://innsbddl2019.org/</a><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">VENUE & ORGANIZATION</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">The<span> </span><span class="gmail-il">2019</span><span> </span><span class="gmail-il">INNS</span><span> </span>Big Data and Deep Learning (</span><span class="gmail-m_435358355094055691m_-7048174159493902673gmail-il" style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">INNSBDDL</span><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline"><span> </span><span class="gmail-il">2019</span>) conference will be held in Sestri Levante, Italy, April 16–18,<span> </span><span class="gmail-il">2019</span>. The conference is organized by the International Neural Network Society, with the aim of representing an international meeting for researchers and other professionals in Big Data, Deep Learning and related areas. It will feature invited plenary talks by world-renowned speakers in the area, in addition to regular and special technical sessions with oral and poster presentations. Moreover, workshops and tutorials will also be featured.</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">IMPORTANT DATES</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Deadline for submission of tutorial and workshop proposals: August 31, 2018</div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Notification of tutorial and workshop proposals: September 30, 2018</div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Deadline of full paper submission: October 31, 2018</div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Notification of paper acceptance: December 31, 2018</div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Camera-ready submission: January 31,<span> </span><span class="gmail-il">2019</span></div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Early registration deadline: January 15,<span> </span><span class="gmail-il">2019</span></div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Registration deadline: January 31,<span> </span><span class="gmail-il">2019</span></div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Conference date: April 16-18,<span> </span><span class="gmail-il">2019</span></div><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">SCOPE</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">We solicit both solid contributions or preliminary results which show the potentiality and the limitations of new ideas, refinements, or contaminations in any aspect of Big Data and Deep Learning. Both theoretical and practical results are welcome.</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Example topics of interest includes but is not limited to the following:</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Big Data Science and Foundations</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Novel Theoretical Models for Big Data</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- New Computational Models for Big Data</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Data and Information Quality for Big Data</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Big Data Mining</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Social Web Mining</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Data Acquisition, Integration, Cleaning, and Best Practices</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Visualization Analytics for Big Data</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Computational Modeling and Data Integration</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Large-scale Recommendation Systems and Social Media Systems</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Cloud/Grid/StreamData Mining</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Big Velocity Data</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Link and Graph Mining</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Semantic-based Data Mining and Data Pre-processing</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Mobility and Big Data</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Multimedia and Multi-structured Data-Big Variety Data</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Modern Practical Deep Networks</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Deep Feedforward Networks</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Regularization for Deep Learning</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Optimization for Training Deep Models</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Convolutional Networks</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Sequence Modeling: Recurrent and Recursive Nets</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Practical Methodology</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Deep Learning Research</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Linear Factor Models</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Autoencoders</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Representation Learning</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Structured Probabilistic Models for Deep Learning</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Monte Carlo Methods</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Confronting the Partition Function</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Approximate Inference</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">- Deep Generative Models</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">PROCEEDINGS & SPECIAL ISSUE</span><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Works submitted as a regular paper will be published in a serie indexed by Scopus. Submitted<span> </span><span class="gmail-il">papers</span><span> </span>will be reviewed by some PC members based on technical quality, relevance, originality, significance and clarity. At least one author of an accepted submission should register to present their work at the conference. Selected<span> </span><span class="gmail-il">papers</span><span> </span>presented at<span> </span><span class="gmail-il">INNS</span><span> </span><span class="gmail-il">BDDL</span><span> </span><span class="gmail-il">2019</span><span> </span>will be included in special issues of top journals in the field (prospected journals: Big Data Research, Transaction on Neural Networks and Learning System, Neurocomputing, etc).</span><br></div>