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<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">Title</span></b><span style="font-size:12.0pt;color:black">: Learning-Based High-Dimensional Query Processing<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">Abstract</span></b><span style="font-size:12.0pt;color:black">: With the emergence of deep learning techniques, more and more applications are utilizing neural embeddings which are high-dimensional
numeric vector representations. A recent example is the retrieval-augmented generation (RAG) for Large Language Model. Accordingly, efficient and effective query processing over high-dimensional vectors is demanded. However, the performance of traditional
methods has approached the bottleneck with the rapid increase of data scale. In this talk, Yifan will introduce his studies that apply machine learning techniques to speeding up commonly used high-dimensional data operations, as well as his future research
plans.<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">Bio</span></b><span style="font-size:12.0pt;color:black">: Yifan Wang is a final-year PhD student in the Department of Computer & Information Science & Engineering at the University of Florida.
His primary research interests focus on database systems, high-dimensional data management, information retrieval and application of AI techniques in these areas. His work has been published on top-tier database and data science conferences.</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><span style="color:#5F5F5F">________________________________________________________________________________</span>
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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">Meeting ID:
</span><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif;color:#252424">235 911 207 256</span><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">
</span><span style="font-family:"Segoe UI",sans-serif;color:#252424"><br>
</span><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">Passcode:
</span><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif;color:#252424">hU2FCX
</span><span style="font-family:"Segoe UI",sans-serif;color:#252424"><o:p></o:p></span></p>
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</span><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424"> United States, Columbus
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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">Phone Conference ID:
</span><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif;color:#252424">703 167 990#
</span><span style="font-family:"Segoe UI",sans-serif;color:#252424"><o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif;color:#252424"><a href="https://dialin.teams.microsoft.com/8f5f7319-0053-4423-a154-4f8b6e7fb7dd?id=703167990" target="_blank"><span style="font-size:10.5pt;color:#6264A7">Find a local number</span></a>
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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">If you encounter issues with this meeting, please visit the Help link. If you are not able to resolve the problems, please contact the meeting organizer to let
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<span style="font-size:10.5pt;color:#6264A7">Meeting options</span></a> <o:p></o:p></span></p>
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<p class="MsoNormal"><span style="color:#5F5F5F">________________________________________________________________________________</span>
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<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">Title</span></b><span style="font-size:12.0pt;color:black">: Learning-Based High-Dimensional Query Processing<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">Abstract</span></b><span style="font-size:12.0pt;color:black">: With the emergence of deep learning techniques, more and more applications are utilizing neural embeddings which are high-dimensional
numeric vector representations. A recent example is the retrieval-augmented generation (RAG) for Large Language Model. Accordingly, efficient and effective query processing over high-dimensional vectors is demanded. However, the performance of traditional
methods has approached the bottleneck with the rapid increase of data scale. In this talk, Yifan will introduce his studies that apply machine learning techniques to speeding up commonly used high-dimensional data operations, as well as his future research
plans.<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">Bio</span></b><span style="font-size:12.0pt;color:black">: Yifan Wang is a final-year PhD student in the Department of Computer & Information Science & Engineering at the University of Florida.
His primary research interests focus on database systems, high-dimensional data management, information retrieval and application of AI techniques in these areas. His work has been published on top-tier database and data science conferences.</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<div>
<p class="MsoNormal"><span style="color:#5F5F5F">________________________________________________________________________________</span>
<span style="mso-ligatures:none"><o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">Meeting ID:
</span><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif;color:#252424">235 911 207 256</span><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">
</span><span style="font-family:"Segoe UI",sans-serif;color:#252424"><br>
</span><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">Passcode:
</span><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif;color:#252424">hU2FCX
</span><span style="font-family:"Segoe UI",sans-serif;color:#252424"><o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424"><a href="https://www.microsoft.com/en-us/microsoft-teams/download-app" target="_blank"><span style="color:#6264A7">Download Teams</span></a> |
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<p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif;color:#252424"><a href="tel:+16147066572,,703167990# "><span style="font-size:10.5pt;color:#6264A7">+1 614-706-6572,,703167990#</span></a>
</span><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424"> United States, Columbus
</span><span style="font-family:"Segoe UI",sans-serif;color:#252424"><o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;color:#252424">Phone Conference ID:
</span><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif;color:#252424">703 167 990#
</span><span style="font-family:"Segoe UI",sans-serif;color:#252424"><o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-family:"Segoe UI",sans-serif;color:#252424"><a href="https://dialin.teams.microsoft.com/8f5f7319-0053-4423-a154-4f8b6e7fb7dd?id=703167990" target="_blank"><span style="font-size:10.5pt;color:#6264A7">Find a local number</span></a>
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<p class="MsoNormal"><span style="color:#5F5F5F">________________________________________________________________________________</span>
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