Statements (33)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:algorithm
|
| gptkbp:advantage |
scalability
parallelizability decomposability |
| gptkbp:convergesTo |
convex problems
|
| gptkbp:field |
gptkb:machine_learning
gptkb:mathematics optimization |
| gptkbp:fullName |
Alternating Direction Method of Multipliers
|
| https://www.w3.org/2000/01/rdf-schema#label |
ADMM
|
| gptkbp:introduced |
gptkb:Douglas
Glowinski Marroco Rachford |
| gptkbp:introducedIn |
1970s
|
| gptkbp:limitation |
parameter tuning required
slow convergence for some problems |
| gptkbp:parameter |
step size
penalty parameter |
| gptkbp:popularFor |
gptkb:signal_processing
image processing statistical learning |
| gptkbp:relatedTo |
augmented Lagrangian method
dual decomposition |
| gptkbp:step |
dual variable update
primal variable update variable splitting |
| gptkbp:usedFor |
large-scale optimization
convex optimization distributed optimization |
| gptkbp:bfsParent |
gptkb:ASEAN_Defence_Ministers'_Meeting
gptkb:Abu_Dhabi_Motorsports_Management |
| gptkbp:bfsLayer |
7
|