Research map / Optimization / Nonconvex and smooth optimization
An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use augmented Lagrangian (with dual variable) instead of pure penalty method | inexact ALM · nonconvex constrained problems | practical convergence | Helped |
| Burer-Monteiro nonconvex iALM instead of convex solvers HCGM and SDPNAL+ | clustering SDP on Fashion-MNIST · clustering SDP, 1000 samples | running time | Helped |
| use second-order trust region solver rather than first-order APGM in the subproblem | inexact ALM · theory | oracle complexity: O~(1/eps^3) first-order oracle calls vs O~(1/eps^5) second-order oracle calls | Mixed |
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