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SUMMARY:Marc Lackenby (University of Oxford)
DTSTART:20230222T140000Z
DTEND:20230222T153000Z
DTSTAMP:20260423T005740Z
UID:bM2L/1
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/bM2L/1/">Usi
 ng machine learning to formulate mathematical conjectures</a>\nby Marc Lac
 kenby (University of Oxford) as part of Barcelona Mathematics and Machine 
 Learning Colloquium Series\n\n\nAbstract\nI will describe how machine lear
 ning can be used as a tool for pure mathematicians to formulate new conjec
 tures. I will initially focus on a discovery of a new connection between t
 wo different areas of low-dimensional topology and geometry. My collaborat
 ors and I were able to use fairly simple supervised learning to establish 
 that the signature of a knot can be predicted from the knot's hyperbolic i
 nvariants. We were able to formulate this relationship as a precise conjec
 ture\, that we eventually proved (in a slightly modified form). The method
  that we used is very general: it is likely to be applicable to many area 
 of mathematics. However\, in my talk\, I will discuss its limitations\, wh
 ich include the difficulty of interpreting the patterns that machine learn
 ing discovers\, as well as the tendency for machine learning algorithms to
  ignore outliers. If there is time\, I will describe some new examples whe
 re machine learning has been able to find unexpected conjectural connectio
 ns in low-dimensional topology.\n
LOCATION:https://researchseminars.org/talk/bM2L/1/
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