<div dir="ltr"><div><span class="" style="white-space:pre"> </span>CALL FOR PAPERS Special Session on</div><div>"Concept Drift, Domain Adaptation & Learning in Dynamic Environments"</div><div><span class="" style="white-space:pre"> </span>which will be held at IJCNN 2016 (within IEEE WCCI 2016),</div><div><span class="" style="white-space:pre"> </span> July 25 - 29, 2016, Vancouver, Canada.</div><div><br></div><div><span class="" style="white-space:pre"> </span><a href="http://home.deib.polimi.it/boracchi/events/ijcnn2016_SS/index.html">http://home.deib.polimi.it/boracchi/events/ijcnn2016_SS/index.html</a></div><div><span class="" style="white-space:pre"> </span><a href="http://www.wcci2016.org/">http://www.wcci2016.org/</a> </div><div><br></div><div>**********************************************************</div><div>IMPORTANT DATES</div><div>Paper submission: January 15th, 2016</div><div>Paper Decision notification: March 15th, 2016</div><div>Camera-ready submission: April 15th, 2016</div><div>Conference Dates: July 25 - 29th, 2016</div><div>***********************************************************</div><div><br></div><div>One of the fundamental goals in computational intelligence is to achieve brain-like intelligence, a remarkable property of which is the ability to incrementally learn from noisy and incomplete data, and ability to adapt to changing environments. The special session aims at presenting novel approaches to incremental learning and adaptation to dynamic environments both from the more traditional and theoretical perspective of computational intelligence and from the more practical and application-oriented one.</div><div><br></div><div>This Special Session aspires at building a bridge between academic and industrial research, providing a forum for researchers in this area to exchange new ideas with each other, as well as with the rest of the neural network & computational intelligence community. </div><div><br></div><div>*Topics*</div><div>Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics:</div><div>• Methodologies, algorithms and techniques for learning in dynamic/non-stationary environments</div><div>• Incremental learning, lifelong learning, cumulative learning</div><div>• Domain adaptation and dataset-shift, covariate-shift adaptation</div><div>• Semi-supervised learning methods for handling concept-drift</div><div>• Ensemble methods for learning under concept drift</div><div>• Learning under concept drift and class unbalance</div><div>• Change-detection tests and anomaly-detection algorithms</div><div>• Algorithms for information mining in nonstationary datastreams</div><div>• Applications that call for learning in dynamic/non-stationary environments, and for incremental learning, such as:</div><div><span class="" style="white-space:pre"> </span>o Adaptive classifiers for concept drift and recurring concepts</div><div><span class="" style="white-space:pre"> </span>o Intelligent systems operating in dynamic/non-stationary environments</div><div><span class="" style="white-space:pre"> </span>o Intelligent embedded and cyber-physical systems</div><div>• Applications that call for change and anomaly detection, such as:</div><div><span class="" style="white-space:pre"> </span>o fault detection</div><div><span class="" style="white-space:pre"> </span>o fraud detection</div><div><span class="" style="white-space:pre"> </span>o network-intrusion detection and security</div><div><span class="" style="white-space:pre"> </span>o intelligent sensor networks</div><div>• Cognitive-inspired approaches to adaptation and learning</div><div>• Development of test-sets benchmarks for evaluating algorithms learning in non-stationary/dynamic environments</div><div>• Issues relevant to above mentioned or related fields</div><div><br></div><div>*Keywords*</div><div>Concept drift, nonstationary environment, change/anomaly detection, domain adaptation, incremental learning, data streams.</div><div><br></div><div><br></div><div>*Paper Submission*</div><div>THE DEADLINE FOR THE PAPER SUBMISSION TO THE SPECIAL SESSION IS THE SAME OF IEEE WCCI 2016, January 15th 2016.</div><div><br></div><div>All the submissions will be peer-reviewed with the same criteria used for other contributed papers.</div><div><br></div><div>Perspective authors will submit their papers through the IEEE IJCNN/WCCI 2016 conference submission system at <a href="http://www.wcci2016.org/">http://www.wcci2016.org/</a></div><div>Please make sure to select the Special Session nr 26 "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" from the "S. SPECIAL SESSION TOPICS" name in the "Main Research topic" dropdown list;</div><div><br></div><div>Templates and instruction for authors will be provided on the IEEE IJCNN/WCCI webpage <a href="http://www.wcci2016.org/">http://www.wcci2016.org/</a></div><div><br></div><div>All papers submitted to the special sessions will be subject to the same peer-review procedure as regular papers, accepted papers will be published in the conference proceedings.</div><div><br></div><div>Further information about IEEE IJCNN/WCCI 2016 can be found at <a href="http://www.wcci2016.org/">http://www.wcci2016.org/</a></div><div><br></div><div>For any question you may have about the Special Session or paper submission, feel free to contact Giacomo Boracchi, <a href="mailto:giacomo.boracchi@polimi.it">giacomo.boracchi@polimi.it</a></div><div><br></div><div><br></div><div>***********************************************************</div><div>Special Session on</div><div>"Concept Drift, Domain Adaptation & Learning in Dynamic Environments" @ IEEE IJCNN/WCCI 2016</div><div><br></div><div>*Organizes*</div><div>. Giacomo Boracchi (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy) <a href="mailto:giacomo.boracchi@polimi.it">giacomo.boracchi@polimi.it</a></div><div>. Robi Polikar (Rowan University, Glassboro, NJ, USA) <a href="mailto:polikar@rowan.edu">polikar@rowan.edu</a></div><div>. Manuel Roveri (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy) <a href="mailto:manuel.roveri@polimi.it">manuel.roveri@polimi.it</a></div><div>. Gregory Ditzler, (University of Arizona, AZ, USA) <a href="mailto:ditzler@email.arizona.edu">ditzler@email.arizona.edu</a></div><div><br></div><div>*Technical Program Committee*</div><div>. Alfred Bifet, University of Waikato, New Zealand</div><div>. Gianluca Bontempi, Université Libre de Bruxelles, Belgium<span class="" style="white-space:pre"> </span></div><div>. Yaochu Jin, University of Surrey, England, UK</div><div>. Georg Krempl, University Magdeburg, Germany</div><div>. Ludmilla Kuncheva, University of Bangor, Wales, UK</div><div>. Leandro L. Minku, University of Birmingham, UK</div><div>. Harris Papadopoulos, Frederick University, Cyprus</div><div>. Leszek Rutkowski, Czestochowa University of Technology, Poland</div><div>. Shiliang Sun, East China Normal University</div><div>. Marley Vellasco, Pontifícia Universidade Católica do Rio de Janeiro, Brasil</div><div>. Shengxiang Yang, Brunel University, England, UK</div><div>***********************************************************</div>
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