KLDiv-class: The KLDiv class.

In CVXR: Disciplined Convex Optimization

The KLDiv class.

Description

The elementwise KL-divergence x\log(x/y) - x + y.

Usage

KLDiv(x, y)

## S4 method for signature 'KLDiv'
to_numeric(object, values)

## S4 method for signature 'KLDiv'
sign_from_args(object)

## S4 method for signature 'KLDiv'
is_atom_convex(object)

## S4 method for signature 'KLDiv'
is_atom_concave(object)

## S4 method for signature 'KLDiv'
is_incr(object, idx)

## S4 method for signature 'KLDiv'
is_decr(object, idx)

## S4 method for signature 'KLDiv'
.grad(object, values)

## S4 method for signature 'KLDiv'
.domain(object)

Arguments

x	An Expression or numeric constant.
y	An Expression or numeric constant.
object	A KLDiv object.
values	A list of numeric values for the arguments
idx	An index into the atom.

Methods (by generic)

• to_numeric(KLDiv): The KL-divergence evaluted elementwise on the input value.

• sign_from_args(KLDiv): The atom is positive.

• is_atom_convex(KLDiv): The atom is convex.

• is_atom_concave(KLDiv): The atom is not concave.

• is_incr(KLDiv): The atom is not monotonic in any argument.

• is_decr(KLDiv): The atom is not monotonic in any argument.

• .grad(KLDiv): Gives the (sub/super)gradient of the atom w.r.t. each variable

• .domain(KLDiv): Returns constraints describng the domain of the node

Slots

x

An Expression or numeric constant.

y

An Expression or numeric constant.

CVXR documentation built on June 27, 2024, 5:11 p.m.