<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
<meta name="Generator" content="Microsoft Word 15 (filtered medium)">
<style><!--
/* Font Definitions */
@font-face
{font-family:"Cambria Math";
panose-1:2 4 5 3 5 4 6 3 2 4;}
@font-face
{font-family:Calibri;
panose-1:2 15 5 2 2 2 4 3 2 4;}
/* Style Definitions */
p.MsoNormal, li.MsoNormal, div.MsoNormal
{margin:0cm;
font-size:11.0pt;
font-family:"Calibri",sans-serif;
mso-fareast-language:EN-US;}
a:link, span.MsoHyperlink
{mso-style-priority:99;
color:#0563C1;
text-decoration:underline;}
span.EmailStyle17
{mso-style-type:personal-compose;
font-family:"Calibri",sans-serif;
color:windowtext;}
.MsoChpDefault
{mso-style-type:export-only;
mso-fareast-language:EN-US;}
@page WordSection1
{size:612.0pt 792.0pt;
margin:70.85pt 70.85pt 70.85pt 70.85pt;}
div.WordSection1
{page:WordSection1;}
--></style><!--[if gte mso 9]><xml>
<o:shapedefaults v:ext="edit" spidmax="1026" />
</xml><![endif]--><!--[if gte mso 9]><xml>
<o:shapelayout v:ext="edit">
<o:idmap v:ext="edit" data="1" />
</o:shapelayout></xml><![endif]-->
</head>
<body lang="SV" link="#0563C1" vlink="#954F72" style="word-wrap:break-word">
<div class="WordSection1">
<p class="MsoNormal"><span lang="EN-US" style="font-size:14.0pt">Welcome to an IDA Machine Learning Seminar on Wednesday, March 22 at 15:15 in BL32 Nobel
<b>(note the place!)</b><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">This seminar is co-organized with the YUIMA stochastic differential equations course. Coffee and cake will be served outside the lecture room from 14:45 and we invite seminar attendees to join us for this as well!<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:14.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:14.0pt">Text Classification with Born’s Rule<o:p></o:p></span></b></p>
<p class="MsoNormal"><i><span lang="EN-US" style="font-size:14.0pt"><a href="https://eguidotti.com/">Emanuele Guidotti</a>, Institute of Financial Analysis, University of Neuchâtel<o:p></o:p></span></i></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Abstract: This paper presents a text classification algorithm inspired by the notion of superposition of states in quantum physics. By regarding text as a superposition of words, we derive the wave function of a document
and we compute the transition probability of the document to a target class according to Born's rule. Two complementary implementations are presented. In the first one, wave functions are calculated explicitly. The second implementation embeds the classifier
in a neural network architecture. Through analysis of three benchmark datasets, we illustrate several aspects of the proposed method, such as classification performance, explainability, and computational efficiency. These ideas are also applicable to non-textual
data. <o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Based on the NeurIPS 2022 paper by Emanuele Guidotti and Alfio Ferrara<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><a href="https://openreview.net/forum?id=sNcn-E3uPHA">https://openreview.net/forum?id=sNcn-E3uPHA</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Location: <b>BL32 Nobel, B building – see
<a href="https://liu.se/polopoly/basfakta/kartor/kartorli/B2.pdf">https://liu.se/polopoly/basfakta/kartor/kartorli/B2.pdf</a></b><o:p></o:p></span></p>
<p class="MsoNormal">Organizers: Fredrik Lindsten, Sourabh Balgi<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> ------------------<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> <o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">The list of future seminars in the series is available at:
</span><a href="http://www.ida.liu.se/research/machinelearning/seminars/" target="_BLANK"><span lang="EN-US">http://www.ida.liu.se/research/machinelearning/seminars/</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">You can subscribe to the seminar series' calendar using this ics link:
<a href="https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Foutlook.office365.com%2Fowa%2Fcalendar%2F4d811ae47ce446f58d11a7c2f50a7ed8%40ad.liu.se%2F0f5253d7bc7841248c71eb4c28eb2d668927992292494627279%2Fcalendar.ics&data=05%7C01%7Cfredrik.lindsten%40liu.se%7C98d44302c2de402ea58908dabd082c24%7C913f18ec7f264c5fa816784fe9a58edd%7C0%7C0%7C638030140200506363%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=pQN7aaYgjYA61y7JQDPphzN5ETwfYySt3pI0UtXefgc%3D&reserved=0" target="_BLANK">
https://outlook.office365.com/owa/calendar/4d811ae47ce446f58d11a7c2f50a7ed8@ad.liu.se/0f5253d7bc7841248c71eb4c28eb2d668927992292494627279/calendar.ics</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> <o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Welcome!<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">IDA Machine Learning Group<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Linköping University<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
</div>
</body>
</html>