Research map / Learning theory and algorithms / Matrix and tensor methods
Power analysis of knockoff filters for correlated designs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use CI-knockoff instead of Equi-knockoff | Knockoff filter · Binary tree, equal correlations | power | No clear effect |
| Use CI-knockoff instead of Equi-knockoff | Knockoff filter · Markov chain, random correlations | power | Helped |
| Use CI-knockoff instead of Equi-knockoff | Knockoff filter · Markov chain, random correlations | scaled ESD (LP distance): 0.9995 -> 0.1075 | Helped |
| Use CI-knockoff instead of Equi-knockoff | Knockoff filter · Binary tree, equal correlations | scaled ESD (LP distance): 0.501 -> 0.002 | Helped |
Closest papers by meaning
- Integral-based Knockoffs Inference for Partially Linear Models (AAAI 2026 · similarity 0.87)
- Error-Based Knockoffs Inference for Controlled Feature Selection (AAAI 2022 · similarity 0.86)
- Knockoffs Inference for Partially Linear Models with Automatic Structure Discovery (AAAI 2025 · similarity 0.84)
- DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection (NeurIPS 2024 · similarity 0.83)
- Conformalized Multiple Testing after Data-dependent Selection (NeurIPS 2024 · similarity 0.82)
- Strong and Weak Identifiability of Optimization-based Causal Discovery in Non-linear Additive Noise Models (ICML 2025 · similarity 0.81)
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