is_stuffed_qp_objective

An object-oriented modeling language for disciplined
convex programming (DCP) as described in Fu, Narasimhan, and Boyd
(2020, <doi:10.18637/jss.v094.i14>). It allows the user to
formulate convex optimization problems in a natural way following
mathematical convention and DCP rules. The system analyzes the
problem, verifies its convexity, converts it into a canonical
form, and hands it off to an appropriate solver to obtain the
solution. Interfaces to solvers on CRAN and elsewhere are
provided, both commercial and open source.

Anqi Fu

CVXR

Disciplined Convex Optimization

Balasubramanian Narasimhan

David W Kang

Steven Diamond

John Miller

Stephen Boyd

Paul Kunsberg Rosenfield

is_stuffed_qp_objective function

<dl><dt>objective</dt>
<dd>A Minimize or Maximize object representing the optimization objective.</dd></dl>

Arguments

Is the QP objective stuffed? — is_stuffed_qp_objective

<dl>

<dt>objective</dt>
<dd>A Minimize or Maximize object representing the optimization objective.</dd>

</dl>

Is the QP objective stuffed?

State of Data and AI Literacy Report 2025

is_stuffed_qp_objective: Is the QP objective stuffed?

Description

Usage

Value

Arguments