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KLDiv-class

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: The KL-divergence evaluted elementwise on the input value.

  • sign_from_args: The atom is positive.

  • is_atom_convex: The atom is convex.

  • is_atom_concave: The atom is not concave.

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

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

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

  • .domain: Returns constraints describng the domain of the node

Slots

x

An Expression or numeric constant.

y

An Expression or numeric constant.


CVXR

Disciplined Convex Optimization

v1.0-10
Apache License 2.0 | file LICENSE
Authors
Anqi Fu [aut, cre], Balasubramanian Narasimhan [aut], David W Kang [aut], Steven Diamond [aut], John Miller [aut], Stephen Boyd [ctb], Paul Kunsberg Rosenfield [ctb]
Initial release

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