Index

Symbols | A | B | C | D | E | F | G | H | I | L | M | N | O | P | Q | R | S | W

Symbols

1-norm
norm
2-norm
norm

A

absolute value, [1]

B

basic notions
linear optimization
basis pursuit
dual problem

C

case studies
Markowitz portfolio optimization
maximum likelihood estimator
complementarity gap
concave function
cone
conic quadratic
dual
rotated conic quadratic, [1], [2]
semidefinite
conic quadratic
duality
modeling
optimization
representable
see also cone
constraint satisfaction
continuous (nonconvex)
piecewise-linear function
convex
function
piecewise-linear function, [1]
set
convex quadratic, [1], [2]
quadratically constraint
set
sets
convex quadratic optimization
curve-fitting

D

determinant
roots of the
disjunctive constraints
domain, [1]
dual
cone
function
norm
problem
problem basis pursuit
problem semidefinite
duality
conic quadratic
linear optimization
semidefinite optimization
duality gap, [1]

E

eigenvalue decomposition
see also spectral factorization
eigenvalue optimization
ellipsoidal set
epigraph, [1], [2]
extremal ellipsoid

F

Farkas certificate, [1], [2], [3]
feasible set, [1]
filter design
fixed charge cost
function
convex
dual

G

geometric mean
geometric mean cone
geometry
linear optimization
Grammian matrix

H

halfspace
harmonic mean
see geometric mean
Hermitian matrices
hyperplane
hypograph

I

ill-posed
indicator variable
infeasibility, [1]
Farkas certificate
conic quadratic optimization
linear optimization
locating
infinity norm
norm
inner product, [1]

L

Lagrange function, [1]
Lagrange multipliers, [1]
lambda method
linear
matrix inequality, [1], [2]
modeling
optimization basic notions
optimization duality
optimization geometry
optimization;
optimization; duality
linear optimization
infeasibility
locating
infeasibility

M

Markowitz portfolio optimization
case studies
matrices
semidefinite
matrix
matrix inequality
linear, [1], [2]
maximum likelihood estimator
case studies
method of
penalization
mixed integer
optimization
mixed integer nonlinear
modeling
conic quadratic
linear

N

nearest correlation matrix
nonnegative polynomials
nonnegative trigonometric polynomials
norm
1-norm
2-norm
dual
infinity norm
nuclear

O

objective function
optimization, [1]
basic notions, linear
conic quadratic
duality, linear
duality, semidefinite
geometry, linear
mixed integer
semidefinite
optimization;
linear

P

pack constraints
partition constraints
penalization
method of
piecewise-linear function
continuous (nonconvex)
convex, [1], [2]
polyhedron
polynomial set
problem
basis pursuit, dual
dual
semidefinite, dual

Q

quadratically constrained
quadratically constraint
convex quadratic

R

rational powers, [1], [2]
relaxations
of binary optimization
representable
conic quadratic
robust optimization
roots of the
determinant
rotated conic quadratic
cone, [1]

S

Schur complement, [1], [2]
second-order cone
semicontinuity
semidefinite
dual problem
matrices, [1], [2]
matrices;properties of
modeling
optimization
optimization duality
semidefinite matrices
semidefinite optimization
separable quadratic optimization
separating hyperplane
set
convex
sets
convex quadratic
singular value optimization, [1], [2]
spectrahedron
spectral factorization, [1], [2]
strong duality, [1], [2], [3]
symmetric positive semidefinite
see semidefinite

W

weak duality, [1], [2], [3]