BEGIN:VCALENDAR VERSION:2.0 PRODID:ILLC Website X-WR-TIMEZONE:Europe/Amsterdam BEGIN:VTIMEZONE TZID:Europe/Amsterdam X-LIC-LOCATION:Europe/Amsterdam BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:19700329T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:19701025T030000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:/NewsandEvents/Archives/2018/newsitem/9611/25- January-2018-Master-of-Science-AI-defense-Peter-De kker DTSTAMP:20180122T134817 SUMMARY:Master of Science AI defense, Peter Dekker DTSTART;TZID=Europe/Amsterdam:20180125T140000 LOCATION:Science Park 107, room F3.20 ATTENDEE;ROLE=Supervisor:dr. Jelle Zuidema and pro f.dr. Gerhard Jäger DESCRIPTION:In my thesis, I applied the machine le arning paradigm, succesful in many computing tasks , to historical linguistics. I proposed the task o f word prediction: by training a machine learning model on pairs of words in two languages, it learn s the sound correspondences between the two langua ges and should be able to predict unseen words. X-ALT-DESC;FMTTYPE=text/html:\n
In my thesis, I applied the machine learning paradigm, succesful in many computing tasks, to historical linguistic s. I proposed the task of word prediction : by training a machine learning model on pairs of words in two languages, it learns the sound corre spondences between the two languages and should be able to predict unseen words.
URL:/NewsandEvents/Archives/2018/newsitem/9611/25- January-2018-Master-of-Science-AI-defense-Peter-De kker CONTACT:Peter Dekker at peter.dekker at student.uv a.nl END:VEVENT END:VCALENDAR