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(July 29th) Convex optimization


Convex optimization


2019.7.29 (월) 10:30


Prof. Stephen P.Boyd(Chair of EE at Stanford Univ.)


W1-3 Applied Engineering B/D, Multimedia Hall (1F)


Convex optimization has emerged useful tool for applications that include data analysis and model fitting resource allocation, engineering design, network design, and optimization, finance, and control signal processing.

After an overview of the mathematics, algorithms, and software framworks for covex optimization, we turn to common themes that arise across applications, such as sparsity and relaxation.

We describe recent work on real-time embedded convex optimization, in which small problems are solved repeatedly in milisecond or micosecond time frams, and large-sclae distributed convex optimization, in which many solvers are coordinated to solve enormous problems.



  • Chair of Department of Electrical Engineering at Standford University
  • Samsung Professor of Engineering
  • Professor of Electrical Engineering
  • Professor of courtesy of Computer Science and Management Science & Engineering.
  • EURASIP Athanasios Papoulis Society Award, 2019
  • Fellow of INFORMS, 2016
  • Fellow of SIAM, 2015
  • Mathmatical Optimaztion Society’s Beale-Orchard-Hays Award, 2012
  • UC Berkeley Outstanding E.E Alumnus Award, 2011
  • AACC Donald P. Eckman Award, 1992
  • National Science Foundation Presidential Young Investigator Award, 1986-91
  • ONR Young Investigator Award, 1985-89