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ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| locally adaptive penalty (LA-SADMM) vs fixed-penalty SADMM | stochastic ADMM for generalized lasso (SVM + GGLASSO) · w8a, gisette | objective vs iterations | Helped |
| locally adaptive penalty (LA-ADMM) vs fixed penalty linearized ADMM | robust regression with low-rank regularizer · synthetic data | objective vs iterations | No clear effect |
| locally adaptive penalty (LA-ADMM) vs fixed penalty linearized ADMM | low-rank representation · shape | objective vs iterations | No clear effect |
| self-adaptive residual-based penalty (ADMM-AP) vs locally adaptive penalty | linearized ADMM baselines · RR+LR and LRR | objective vs iterations | Hurt |
| theoretical complexity: adaptive penalty (deterministic) vs fixed penalty ADMM | ADMM for structured non-smooth problems · theory, local error bound exponent theta | iteration complexity: O(1/eps) to O(1/eps^(1-theta)) | Helped |
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