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Stable Prediction with Model Misspecification and Agnostic Distribution Shift
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use DWR's jointly optimized decorrelation weights and weighted regression instead of OLS | Linear regression under model misspecification · Synthetic S ⟂ V, Y_poly; n=2000, p=10, r=1.7 | Stability_Error: 0.090 -> 0.012 | Helped |
| Use DWR's jointly optimized decorrelation weights and weighted regression instead of OLS | Linear regression under model misspecification · Synthetic S ⟂ V, Y_poly; n=2000, p=10, r=1.7 | Average_Error: 0.514 -> 0.473 | Helped |
| Use DWR's jointly optimized decorrelation weights and weighted regression instead of OLS | Linear regression under model misspecification · Synthetic S ⟂ V, Y_poly; n=2000, p=10, r=1.7 | β_S_Error: 0.887 -> 0.581 | Helped |
| Use DWR's jointly optimized decorrelation weights and weighted regression instead of OLS | Linear regression under model misspecification · Synthetic S ⟂ V, Y_poly; n=2000, p=10, r=1.7 | β_V_Error: 0.332 -> 0.077 | Helped |
| Use decorrelation reweighting rather than standard baselines | Prediction across unknown test environments · Synthetic test environments with r_test > 1.3 and r_train=1.7 | RMSE | Hurt |
| Use decorrelation reweighting rather than standard baselines | Prediction across unknown test environments · Synthetic test environments with r_test < -1.3 and r_train=1.7 | RMSE | Helped |
| Use decorrelation reweighting rather than standard baselines | Air-quality prediction across 10 U.S. states · PM10 prediction; train on State 1, test on all 10 States | RMSE | Mixed |
Closest papers by meaning
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- Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments (ICML 2025 · similarity 0.83)
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