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