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Interior-point methods (also referred to as barrier methods or IPMs) are algorithms for solving linear and non-linear convex optimization problems. IPMs combine two advantages of previously-known algorithms:
History, Path-following methods & Primal-dual methods
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displaystyle method methods barrier function convex solution interior program minimize newton number linear path-following feasible point problem quad subject steps
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Newton's method becomes longer | instance of | The run-time of solvers | 0.80 | text |
| and it is hard to prove that the total runtime is polynomial.Renegar | instance of | The run-time of solvers | 0.80 | text |
| Gonzaga proved that a specific instance of a path-following method is polytime | instance of | The run-time of solvers | 0.80 | text |
| Interior-point method | has method | Here | 0.60 | section |
| Interior-point method | related to history | An | 0.60 | section |
| Interior-point method | related to history | Soviet | 0.60 | section |
| Interior-point method | related to history | Dikin | 0.60 | section |
| Interior-point method | related to history | The | 0.60 | section |
| Interior-point method | related to history | In | 0.60 | section |
| Interior-point method | related to history | Narendra Karmarkar | 0.60 | section |
| Interior-point method | related to history | Karmarkar's | 0.60 | section |
| Interior-point method | related to history | L-bit | 0.60 | section |
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