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<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB">***apologies if you receive this more than once***<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Turing at Southampton is pleased to announce a new Seminar Series – details of the first two seminars taking place in January are below. All are welcome to attend!<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b><span style="color:black">Speaker:</span></b><span style="color:black"> Shotaro Shiba-Funai, Okinawa Institute of Science and Technology<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Date: </span>
</b><span style="color:black">Friday 17 January 2020, 12.00 noon<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Location:</span></b><span style="color:black"> Building 46/5081<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Title:</span></b><span style="color:black"> Feature extraction by machine learning and its related physics<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Abstract: </span><o:p></o:p></b></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span style="color:black">Unsupervised machine learning is generally useful to extract features of input data. Since it can be regarded as a kind of information compression, some researchers suggest its similarity to coarse-graining and
renormalization.<b><o:p></o:p></b></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span style="color:black">In this talk, we use spin configurations of Ising model as the input data and restricted Boltzmann machine (RBM) as the method of unsupervised learning. Then we look at what kind of features the machine extracts,
using our method of “RBM flow”. As a result, we can find an interesting similarity to renormalization and some coincidence with thermodynamics. However, we also discover apparent differences from renormalization and then argue why such phenomena occur by
studying the parameter dependence in machine learning.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="color:black">***********************************************<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Speaker: </span></b><span style="color:black"> James Burridge, University of Portsmouth<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Date:</span></b><span style="color:black"> Wednesday 29 January 2020, 15.00<b><o:p></o:p></b></span></p>
<p class="MsoNormal"><b><span style="color:black"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span style="color:black">Location: </span></b><span style="color:black">Building 54/5025<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="color:black">Title:</span></b><span style="color:black"> Language Mechanics <o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal" style="margin-left:72.0pt;text-indent:-72.0pt"><b><span style="color:black">Abstract:</span></b><span style="color:black"> </span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span style="color:black">Language is one of the primary “signals” emitted by society - a good place to start
</span>i<span style="color:black">f</span> <span style="color:black">we</span> <span style="color:black">
want a mathematical understanding human collective behavior. In this talk I will explore how the tools of statistical physics can be used to model language evolution. First, I will describe a connection between phase ordering in magnetic systems, and the geographical
evolution of language. I will show how different universality classes in physical models correspond to alternative hypotheses for the social factors which drive language change, with some models able to predict observed patterns. I will then explore the sound
inventories from which languages are built, specifically vowels. Human vowel systems may be shown to spontaneously emerge from a “soup” of diffusing words, modelled as Brownian particles. If we want such diffusive dynamics to accurately fit real linguistic
data, then we can again make use of phase ordering models, treating the evolution of sound inventories as an energy minimization process. Finally, I will discuss how a combination of statistical physics and statistical learning might in future allow us to
build models with realistic dynamics which fit complex linguistic datasets.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB">_____________________________________________<o:p></o:p></span></p>
<p class="MsoNormal"><b><span style="mso-fareast-language:EN-GB">Susan Davies<o:p></o:p></span></b></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB">Coordination Manager,
<a href="https://www.southampton.ac.uk/wsi/index.page?">Web Science Institute</a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB">University Liaison Manager,
<a href="https://www.southampton.ac.uk/wsi/alan-turing-institute/alan-turing-institute.page">
The Alan Turing Institute</a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB">Room 3041, Building 32<o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB">Web Science Institute<o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB">University of Southampton<o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB">Southampton SO17 1BJ<o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB">023 8059 3523 | 07768 266464<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
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