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SUMMARY:From embedded real-time to large-scale distributed
DTSTART:20120328T161500
DTEND:20120328T173000
DTSTAMP:20260502T121733Z
UID:19b618294e8676131d98295621a027b3a08b0753512ccd5e5f8e0930
CATEGORIES:Conferences - Seminars
DESCRIPTION:Pr. S. Boyd\, Information Systems Laboratory\, Department of E
 lectrical Engineering\, Stanford University\, USA\nConvex optimization has
  emerged as useful tool for applications that include data analysis and mo
 del fitting\, resource allocation\, engineering design\, network design an
 d optimization\, finance\, and control and signal processing. After an ove
 rview\, the talk will focus on two extremes: real-time embedded convex opt
 imization\, and distributed convex optimization.   Code generation can b
 e used to generate extremely efficient and reliable solvers for small prob
 lems\, that can execute in milliseconds or microseconds\, and are ideal fo
 r embedding in real-time systems.  At the other extreme\, we describe met
 hods for large-scale distributed optimization\, which coordinate many solv
 ers to solve enormous problems.
LOCATION:INJ218 http://plan.epfl.ch/?lang=en&room=IN+J218
STATUS:CONFIRMED
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