Convex Optimization (Non-linear): Difference between revisions
Jump to navigation
Jump to search
(Created page with "{{DISPLAYTITLE:Convex Optimization (Non-linear) (Convex Optimization (Non-linear))}} == Description == Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets. == Parameters == No parameters found. == Table of Algorithms == Currently no algorithms in our database for the given problem. == Time Complexity graph == 1000px == Space...") |
No edit summary |
||
(4 intermediate revisions by the same user not shown) | |||
Line 6: | Line 6: | ||
== Parameters == | == Parameters == | ||
$n$: number of variables | |||
$m$: number of constraints | |||
$L$: length of input, in bits | |||
== Table of Algorithms == | == Table of Algorithms == | ||
Line 12: | Line 16: | ||
Currently no algorithms in our database for the given problem. | Currently no algorithms in our database for the given problem. | ||
== Time Complexity | == Time Complexity Graph == | ||
[[File:Convex Optimization (Non-linear) - Time.png|1000px]] | [[File:Convex Optimization (Non-linear) - Time.png|1000px]] | ||
Latest revision as of 09:07, 28 April 2023
Description
Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets.
Parameters
$n$: number of variables
$m$: number of constraints
$L$: length of input, in bits
Table of Algorithms
Currently no algorithms in our database for the given problem.