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SUMMARY:Learning Tensors and Random Matrix Theory - Mehrnoosh Sadrzadeh (U
 CL)
DTSTART:20200228T120000Z
DTEND:20200228T130000Z
UID:TALK135310@talks.cam.ac.uk
CONTACT:James Thorne
DESCRIPTION:Type-driven compositional distributional semantics interprets 
 grammatical types of a system such as the CCG as tensor spaces and words o
 f that type as elements therein. It offers a canonical way of composing th
 e tensors\, via tensor contraction. There is much less known about the cha
 racteristics of the tensors: is there a canonical way of building them and
  what statistical rules govern their distribution? Based on recent joint w
 ork with Wijnholds and Clark and with Kartsaklis\, Ramgoolam and Sword\, w
 e provide some answers.
LOCATION:FW26\, Computer Laboratory
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