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DTSTART:20180325T030000
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DTSTAMP:20260427T100734Z
UID:58ac12da8e020324652463@ist.ac.at
DTSTART:20171108T170000
DTEND:20171108T183000
DESCRIPTION:Speaker: Michael I. Jordan\nhosted by Tom Henzinger\nAbstract: 
 The rapid growth in the size and scope of datasets in science and technolo
 gy has created a need for novel foundational perspectives on data analysis
  that blendthe inferential and computational sciences. That classical pers
 pectives from these fields are not adequate to address emerging problems i
 n Data Science is apparent from their sharply divergent nature at an eleme
 ntary level---in computer science\, the growth of the number of data point
 s is a source of "complexity" that must be tamed via algorithms or hardwar
 e\, whereas in statistics\, the growth of the number of data points is a s
 ource of "simplicity" in that inferences are generally stronger and asympt
 otic results can be invoked. On a formal level\, the gap is made evident b
 y the lack of a role for computational concepts such as "runtime" in core 
 statistical theory and the lack of a role for statistical concepts such as
  "risk" in core computational theory. I present several research vignettes
  aimed at bridging computation and statistics\, including the problem of i
 nference under privacy and communication constraints\, and including a sur
 prising cameo role for symplectic geometry.Please register here (http://is
 t.ac.at/jordan/) by October 31. 
LOCATION:Raiffeisen Lecture Hall\, Central Building\, ISTA
ORGANIZER:aeller@ist.ac.at
SUMMARY:Michael I. Jordan: IST Lecture: On Computational Thinking\, Inferen
 tial Thinking and Data Science
URL:https://talks-calendar.ista.ac.at/events/333
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