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Dear All,</div>
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Thank you for coming to my talk today and I apologize for the really long 20 minutes delay due to the screen needing a restart.</div>
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I hope you found it interesting and please find my slides attached. </div>
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I am open for collaborations on any of the directions I presented or any others if you think it might be relevant.</div>
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Kind regards,</div>
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Erkan</div>
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<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> Vu.ml.seminar.beta <vu.ml.seminar.beta-bounces@listserver.vu.nl> on behalf of Daza Cruz, D.F. (Daniel) via Vu.ml.seminar.beta <vu.ml.seminar.beta@listserver.vu.nl><br>
<b>Sent:</b> Wednesday, December 3, 2025 3:14 PM<br>
<b>To:</b> _list_vu.ml.seminar.beta <vu.ml.seminar.beta@listserver.vu.nl><br>
<b>Subject:</b> [VU ML Seminar] Next meeting: Erkan Karabulut on Scalable Neurosymbolic Knowledge Discovery</font>
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Dear colleagues,</div>
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We are pleased to invite you to the next meeting of the <a data-auth="NotApplicable" data-linkindex="0" rel="noopener noreferrer" title="https://sites.google.com/view/vumls/home" class="x_OWAAutoLink" id="OWA90093d12-0a29-37e0-fc8d-0b9c5c83ec77" target="_blank" href="https://sites.google.com/view/vumls/home" originalsrc="https://sites.google.com/view/vumls/home" style="margin:0px">
VU ML Seminar</a>. This is also the last meeting of the year before we go on an end-of-year break.<br>
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Our next speaker is <b>Erkan Karabulut</b>, who will talk about <b>Scalable Neurosymbolic Knowledge Discovery from Tabular Data.</b></div>
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Erkan is a PhD candidate at the <a title="https://indelab.org/" href="https://indelab.org/" originalsrc="https://indelab.org/">
Intelligent Data Engineering Lab</a> at the University of Amsterdam, and currently he is doing a research visit at Amsterdam UMC.</div>
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<b>Abstract:</b></div>
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Discovering patterns from data in human-understandable forms is a valuable task for both knowledge discovery and interpretable inference. A prominent method is Association Rule Mining (ARM), which identifies patterns in the form of logical rules describing
relationships between data attributes. Popular ARM methods, however, rely on algorithmic or optimization-based solutions that struggle to scale to high-dimensional datasets (i.e., tables with many columns) without effective search space reduction.<br>
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This talk introduces Aerial+, a novel ARM method that leverages neural networks’ ability to handle high-dimensional data to learn a concise set of prominent patterns from tabular datasets. Aerial+ has been evaluated on both digital twin datasets (sensor data
enriched with semantics) and on generic tabular datasets, demonstrating its versatility across domains. In addition, Aerial+ can incorporate prior knowledge to enhance discovery: either from knowledge graphs (structured semantic information about a domain)
or from tabular foundation models, large pre-trained neural networks that capture table semantics and support diverse downstream tasks.</div>
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The meeting will take place on <b>Monday 8 Dec. at 10:00 in room NU-3A57</b>. We hope to see many of you there!</div>
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The organizers,</div>
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Daniel & Zhao</div>
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VU ML Seminar | Schedule: sites.google.com/view/vumls/home</div>
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Manage your subscription: listserver.vu.nl/mailman/options/vu.ml.seminar.beta</div>
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