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Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use Stein repulsive kernel force (MOO-SVGD) instead of Langevin noise (MOO-LD) | multi-objective sampling · MaF1 tri-objective | hypervolume: 0.2613 -> 0.5867 | Helped |
| MOO-SVGD vs EPO with preference vectors | gradient-based MOO · MaF1 tri-objective | hypervolume: 0.5714 -> 0.5867 | Helped |
| MOO-SVGD vs EPO, PF-SMG, COSMOS and hypervolume optimization | ZDT1-3 · ZDT bi-objective | hypervolume over wall-clock time | Helped |
| MOO-SVGD vs EPO and PF-SMG on fairness trade-off | linear classifier · accuracy vs CV score | Pareto front quality | Helped |
| vary kernel bandwidth h and number of particles (ablation) | MOO-SVGD · ZDT1 | final hypervolume | Mixed |
| vary temperature alpha (ablation) | MOO-SVGD · ZDT1 | final hypervolume | Mixed |
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