Man pages for convexjlr
Disciplined Convex Programming in R using Convex.jl

addConstraintAdd constraints to optimization problem
cvx_optimSolve optimization problem
dotInner product
dotsortInner product of two vectors after sorted
entropysum(-x * log(x))
ExprCreate expressions to be used for optimization problem...
geomeanGeometric mean of x and y
huberHuber loss
JMake a variable to be of Julia's awareness
lambdamaxLargest eigenvalues of x
lambdaminSmallest eigenvalues of x
logdetLog of determinant of x
logisticlosslog(1 + exp(x))
matrixfracx^T P^-1 x
maximumLargest elements
minimumSmallest elements
negNegative parts
normp-norm of x
nuclearnormSum of singular values of x
operatornormLargest singular value of x
posPositive parts
problem_creatingCreate optimization problem
propertyGet properties of optimization problem
quadformx^T P x
setupDoing the setup for the package convexjlr
squareSquare of x
sumlargestSum of the largest elements
sumsmallestSum of the smallest elements
sumsquaresSum of squares of x
trTrace of matrix
valueGet values of expressions at optimizer
variable_creatingCreate variable for optimization problem
vecVector representation
vecdotInner product of vector representation of two matrices
vecnormp-norm of vector representation of x
convexjlr documentation built on June 23, 2017, 4:45 a.m.