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<span style="margin:0px;font-size:12pt;background-color:rgb(255, 255, 255)">--- (Apologies for cross-posting; please pass along to any colleagues and students you think may be interested.) ---</span>
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<div style="margin:0px;font-size:12pt;background-color:rgb(255, 255, 255)">SPECIAL SESSION ON
<div style="margin:0px">“Human-in-the-loop Learning System and its User-centric Methods”</div>
<div style="margin:0px">The 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2021)</div>
<div style="margin:0px">October 17-20, 2021 – Melbourne, Australia</div>
<div style="margin:0px"> (Code jgrt6)</div>
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<b><span lang="EN-GB" style="margin:0px;color:black">DEADLINES </span></b></p>
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<span lang="EN-GB" style="margin:0px;color:black">April 19, 2021: deadline for paper submission (Extended) </span></p>
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<span lang="EN-GB" style="margin:0px;color:black">May 26, 2021: notification of paper acceptance/rejection </span></p>
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<span lang="EN-GB" style="margin:0px;color:black">July 12, 2021: deadline for final camera-ready papers. </span></p>
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<span lang="EN-GB" style="margin:0px;color:black">Session Organizers:</span></p>
<div style="margin:0px">Dr. Junpei Zhong – The Hong Kong Polytechnic University, Hong Kong</div>
<div style="margin:0px">Prof. Ahmad Lotfi – Nottingham Trent University, UK</div>
<div style="margin:0px">Dr. David Ada Adama – Nottingham Trent University, UK</div>
<div style="margin:0px">Dr. Weihong Chin – Tokyo Metropolitan University, Japan</div>
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<div style="margin:0px">Session area:</div>
<div style="margin:0px">Human-Machine Systems</div>
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<div style="margin:0px">Session description:</div>
<div style="margin:0px">Human-in-the-Loop (HIL) means including human feedback into the training loop of the machine learning models to improve the quality of training and to augment the functions of the model. The key research problems in algorithms are how
we can evaluate the uncertainty of a model’s prediction? How to leverage both active learning from a human and the optimization of the models? When we use hierarchical reinforcement learning, how can we achieve the goals when the reward is sparse? In sum,
we should find an optimal solution to the trade-off between the model’s accuracy and efficiency in designing the HIL algorithms.</div>
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<div style="margin:0px">Apart from the algorithm design, another key issue in HIL research is from a user-centric perspective, in both data collection and model evaluation steps. Since the quality of the training datasets is also extremely important, how to
integrate multi-modal data from the users with different sensing techniques, such as smart gloves made by flexible sensors, portable eye-trackers, portable brain imaging techniques, is another problem. How can we design the users’ subjective evaluation based
on multi-modal signals? Furthermore, proper designs the interaction between machines and human could also relate to HCI and UX/UI fields etc.</div>
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<div style="margin:0px">This special session is a follow-up session of “HIL machine learning and its applications” in SMC2020. We offer an opportunity for researchers and practitioners in diverse fields from machine learning, robotics, designers or end-users
to join the discussion.</div>
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<div style="margin:0px">A selection of the accepted papers is welcomed to submit their extended versions to a special issue of a journal we edit later this year, subject to rigorous peer review.</div>
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<div style="margin:0px">Topics of interest include, but are not limited to:</div>
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<div style="margin:0px">• Human-Centric Design for Robots or other Intelligent Devices</div>
<div style="margin:0px">• Human Guided Reinforcement Learning</div>
<div style="margin:0px">• Human-robot Collaboration</div>
<div style="margin:0px">• Human-robot Social Interaction</div>
<div style="margin:0px">• Dialogue Systems with Human-in-the-loop</div>
<div style="margin:0px">• Interpretable Machine Learning with Human-in-the-loop</div>
<div style="margin:0px">• Active Learning and Continuous Learning</div>
<div style="margin:0px">• Learning by Demonstration</div>
<div style="margin:0px">• Human Factors in HCI/HRI</div>
<div style="margin:0px">• etc.</div>
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<div style="margin:0px">SUBMISSION</div>
<div style="margin:0px">Papers must be submitted electronically for peer review through PaperCept by April 5, 2021: https://conf.papercept.net/conferences/scripts/start.pl. In PaperCept, click on the SMC 2021 link “Submit a contribution to SMC 2021” and follow
the steps. (Code jgrt6)</div>
<div style="margin:0px">All papers must be written in English and should describe the original work. For guidelines, please follow the SMC website link http://ieeesmc2021.org/call-for-papers/</div>
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<div style="margin:0px">DEADLINES</div>
<div style="margin:0px">April 19, 2021: deadline for paper submission</div>
<div style="margin:0px">May 26, 2021: notification of paper acceptance/rejection</div>
<span style="margin:0px">July 12, 2021: deadline for final camera-ready papers.</span></div>
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