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<span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; display: inline !important; color: rgb(0, 0, 0);">Dear All,</span><br style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; color: rgb(0, 0, 0);">
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<span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; color: rgb(0, 0, 0);">Today , at 1:00 PM EDT, we will have a Cake Seminar given by Jack Araz of<span> </span></span><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; display: inline !important; color: rgb(0, 0, 0);">ODU
and Jlab in the room F224/225. Please, see below for title and abstract.</span><br style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; color: rgb(0, 0, 0);">
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<span style="font-size:11pt;margin:0px"><span style="font-family: Calibri, sans-serif; margin: 0px; background-color: white;"><b><u><span style="font-size:12pt;margin:0px"><span data-markjs="true" class="x_ContentPasted0" style="font-size:11pt;margin:0px"><span data-markjs="true" class="markwfjcj015h" data-ogac="" data-ogab="" data-ogsc="" data-ogsb="">Cake</span></span></span><span style="margin:0px"><span class="x_ContentPasted0" style="margin:0px"> </span></span><span style="font-size:12pt;margin:0px"><span data-markjs="true" class="x_ContentPasted0" style="font-size:11pt;margin:0px"><span data-markjs="true" class="mark5ixy0umrn" data-ogac="" data-ogab="" data-ogsc="" data-ogsb="">Seminar</span></span></span></u></b><span class="x_ContentPasted0" style="margin:0px"><span class="x_ContentPasted0">:</span><b> </b></span><span class="x_ContentPasted0" style="margin:0px">Wednesday,<span> </span></span><span class="x_ContentPasted0" style="margin:0px"><span style="margin:0px"><span style="margin: 0px; color: rgb(36, 36, 36); background-color: white;">November</span><span><span> </span>1</span></span><span><sup>st</sup> </span><span style="margin:0px">,
1pm EDT </span></span></span></span></div>
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<b><u><span class="x_ContentPasted0" style="font-size:11pt;margin:0px">Speaker</span></u></b><span class="x_ContentPasted0 ContentPasted1" style="font-size:11pt;margin:0px">: Jack Araz (ODU/Jlab)<span class="x_ContentPasted0" style="margin:0px"></span></span></p>
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<b><u>Title:</u></b><span> </span>Theory-driven Quantum Machine Learning for HEP<br class="ContentPasted0">
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<b><u>Abstract:</u></b><span> </span>Machine Learning is, in most cases, powerful but a black-box application. In this talk, we will tackle this very problem from a quantum mechanics point of view, arguing that an optimisation problem, such as classification
or anomaly detection, can be studied by “rephrasing" the problem as a quantum many-body system or a mixed state. Such an approach allows us to employ the entire arsenal of quantum theory for data analysis techniques. Hence, this talk will present a small step
towards fully theory-driven and interpretable quantum machine learning applications.<br>
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Best regards,<br>
Caroline, Joe & Zheng-Yan<br>
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