mlsanityData to 7 Oct 2026

Fast and More Powerful Selective Inference for Sparse High-order Interaction Model

arXiv 2106.04929 ↗First posted 9 Jun 2021stat.ML cs.LGcited by 15

Not on the map. Why?

Abstract (arXiv)

Automated high-stake decision-making such as medical diagnosis requires models with high interpretability and reliability. As one of the interpretable and reliable models with good prediction ability, we consider Sparse High-order Interaction Model (SHIM) in this study. However, finding statistically significant high-order interactions is challenging due to the intrinsic high dimensionality of the combinatorial effects. Another problem in data-driven modeling is the effect of "cherry-picking" a.k.a. selection bias. Our main contribution is to extend the recently developed parametric programming approach for selective inference to high-order interaction models. Exhaustive search over the cherry tree (all possible interactions) can be daunting and impractical even for a small-sized problem. We introduced an efficient pruning strategy and demonstrated the computational efficiency and statistical power of the proposed method using both synthetic and real data.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 15 of its 36 references that are in the map. First posted on arXiv 9 Jun 2021.

Builds on

15 of 36 references.

References · 15

  1. 2013Exact post-selection inference, with application to the lassocited by 90
  2. 2014Optimal Inference After Model Selectioncited by 63
  3. 2014Exact Post-Selection Inference for Sequential Regression Procedurescited by 47
  4. 2017Valid Inference Corrected for Outlier Removalcited by 25
  5. 2021More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programmingcited by 24
  6. 2018More powerful post-selection inference, with application to the Lassocited by 22
  7. 2016Selective Inference for Group-Sparse Linear Modelscited by 21
  8. 2018Post-Selection Inference for Changepoint Detection Algorithms with Application to Copy Number Variation Datacited by 19
  9. 2014Selecting the number of principal components: estimation of the true rank of a noisy matrixcited by 18
  10. 2014A significance test for forward stepwise model selectioncited by 17
  11. 2015Selective Sequential Model Selectioncited by 16
  12. 2016Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Miningcited by 13
3 more
  1. 2015Selective inference in regression models with groups of variablescited by 9
  2. 2016Integrative Methods for Post-Selection Inference Under Convex Constraintscited by 7
  3. 2018WHInter: A Working set algorithm for High-dimensional sparse second order Interaction modelscited by 3

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 5; 2024: 4; 2025: 3.

15 papers.

Sort:

  1. 2023Valid P-Value for Deep Learning-Driven Salient Regioncited by 17
  2. 2023CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inferencecited by 10
  3. 2021Exact Statistical Inference for the Wasserstein Distance by Selective Inferencecited by 7
  4. 2024Statistical Test for Feature Selection Pipelines by Selective Inferencecited by 3
  5. 2024Statistical Test for Auto Feature Engineering by Selective Inferencecited by 3
  6. 2025Quantifying Statistical Significance of Deep Nearest Neighbor Anomaly Detection via Selective Inferencecited by 3
  7. 2023Efficient Model Selection for Predictive Pattern Mining Model by Safe Pattern Pruningcited by 2
  8. 2023Feature Importance Measurement based on Decision Tree Samplingcited by 2
  9. 2024Statistical Inference for Feature Selection after Optimal Transport-based Domain Adaptationcited by 2
  10. 2025Statistical Inference for Autoencoder-based Anomaly Detection after Representation Learning-based Domain Adaptationcited by 2
  11. 2022A Confidence Machine for Sparse High-Order Interaction Modelcited by 1
  12. 2023Bounded P-values in Parametric Programming-based Selective Inferencecited by 1
3 more
  1. 2024Statistical Test for Diffusion-Based Anomaly Localization via Selective Inferencecited by 1
  2. 2022Statistical Inference for the Dynamic Time Warping Distance, with Application to Abnormal Time-Series Detectioncited by 0
  3. 2025Statistical Inference for Clustering-based Anomaly Detectioncited by 0