Convex Optimization

E451067

Convex Optimization is a widely used graduate-level textbook that systematically develops the theory, algorithms, and applications of convex optimization problems in engineering, statistics, and applied mathematics.

Try in SPARQL Jump to: Statements Referenced by

Statements (45)

Predicate Object
instanceOf graduate-level textbook
textbook
applicationArea circuit design
communications engineering
control systems
finance
machine learning
signal processing
statistics
author Lieven Vandenberghe NERFINISHED
Stephen Boyd NERFINISHED
emphasis modeling of optimization problems
practical algorithms
field applied mathematics
convex optimization
engineering
optimization
statistics
hasOnlineResources yes
language English
level graduate
notableFor influence in engineering and applied mathematics education
systematic treatment of convex optimization
publisher Cambridge University Press NERFINISHED
structure algorithms
applications
theory
topic Karush–Kuhn–Tucker conditions NERFINISHED
Lagrange duality NERFINISHED
cone programming
convex functions
convex optimization problems
convex sets
duality theory
ellipsoid method
geometric programming
gradient methods
interior-point methods
least-squares problems
linear programming
proximal methods
quadratic programming
semidefinite programming
subgradient methods
usedAs university course textbook

Referenced by (1)

Full triples — surface form annotated when it differs from this entity's canonical label.

Stephen P. Boyd notableWork Convex Optimization