All functions
|
Expr()
|
Create expressions to be used for optimization problem creation |
J()
|
Make a variable to be of Julia's awareness |
addConstraint()
|
Add constraints to optimization problem |
convex_setup()
|
Doing the setup for the package convexjlr |
cvx_optim()
|
Solve optimization problem |
dot()
|
Inner product |
dotsort()
|
Inner product of two vectors after sorted |
entropy()
|
sum(-x * log(x)) |
geomean()
|
Geometric mean of x and y |
huber()
|
Huber loss |
lambdamax()
|
Largest eigenvalues of x |
lambdamin()
|
Smallest eigenvalues of x |
logdet()
|
Log of determinant of x |
logisticloss()
|
log(1 + exp(x)) |
logsumexp()
|
log(sum(exp(x))) |
matrixfrac()
|
x^T P^-1 x |
maximum()
|
Largest elements |
minimum()
|
Smallest elements |
neg()
|
Negative parts |
norm()
|
p-norm of x |
nuclearnorm()
|
Sum of singular values of x |
operatornorm()
|
Largest singular value of x |
pos()
|
Positive parts |
minimize() maximize() satisfy()
|
Create optimization problem |
status() optval()
|
Get properties of optimization problem |
quadform()
|
x^T P x |
square()
|
Square of x |
sumlargest()
|
Sum of the largest elements |
sumsmallest()
|
Sum of the smallest elements |
sumsquares()
|
Sum of squares of x |
tr()
|
Trace of matrix |
value()
|
Get values of expressions at optimizer |
Variable() Semidefinite()
|
Create variable for optimization problem |
vec()
|
Vector representation |
vecdot()
|
Inner product of vector representation of two matrices |
vecnorm()
|
p-norm of vector representation of x |