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BEGIN:VEVENT
UID:c55b57fa69bf9e3af87451a2d85991a9
CATEGORIES:Special Seminar
CREATED:20250220T082322
SUMMARY:Mathematical Data Science
LOCATION:Hill 423
DESCRIPTION:Abstract: Can machine learning help discover new mathematical structures? I
 n this talk we discuss an approach to doing this which one can call "mathem
 atical data science". This paradigm involves studying mathematical objects 
 collectively rather than individually by constructing datasets and conducti
 ng machine learning experiments and interpretations. After an overview, I w
 ill present two case studies: (1) murmurations in number theory and (2) loa
 dings of partitions related to Kronecker coefficients in representation the
 ory and combinatorics. This talk is based on my joint article (arXiv:2502.0
 8620) with Michael Douglas.
X-ALT-DESC;FMTTYPE=text/html:<div data-olk-copy-source="MessageBody" style="font-style: normal; font-wei
 ght: 400; letter-spacing: normal; text-align: start; text-indent: 0px; text
 -transform: none; white-space: normal; word-spacing: 0px; text-decoration: 
 none; border: 0px; font-size: 11pt; line-height: inherit; font-family: Apto
 s, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif;
  margin: 0px; padding: 0px; vertical-align: baseline; color: black; directi
 on: ltr;">Abstract: Can machine learning help discover new mathematical str
 uctures? In this talk we discuss an approach to doing this which one can ca
 ll "mathematical data science". This paradigm involves studying mathematica
 l objects collectively rather than individually by constructing datasets an
 d conducting machine learning experiments and interpretations. After an ove
 rview, I will present two case studies: (1) murmurations in number theory a
 nd (2) loadings of partitions related to Kronecker coefficients in represen
 tation theory and combinatorics. This talk is based on my joint article (ar
 Xiv:2502.08620) with Michael Douglas.</div>
CONTACT:Kyu-Hwan Lee
DTSTAMP:20260829T131203
DTSTART;TZID=America/New_York:20250306T153000
DTEND;TZID=America/New_York:20250306T163000
SEQUENCE:0
TRANSP:OPAQUE
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