Post Selection Inference with Kernels
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Abstract (arXiv)
We propose a novel kernel based post selection inference (PSI) algorithm, which can not only handle non-linearity in data but also structured output such as multi-dimensional and multi-label outputs. Specifically, we develop a PSI algorithm for independence measures, and propose the Hilbert-Schmidt Independence Criterion (HSIC) based PSI algorithm (hsicInf). The novelty of the proposed algorithm is that it can handle non-linearity and/or structured data through kernels. Namely, the proposed algorithm can be used for wider range of applications including nonlinear multi-class classification and multi-variate regressions, while existing PSI algorithms cannot handle them. Through synthetic experiments, we show that the proposed approach can find a set of statistically significant features for both regression and classification problems. Moreover, we apply the hsicInf algorithm to a real-world data, and show that hsicInf can successfully identify important features.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Oct 2016.
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Citing papers per year: 2021: 3; 2022: 2; 2023: 3; 2024: 1; 2025: 3; 2026: 1.
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- 2022Efficient Aggregated Kernel Tests using Incomplete U-statisticscited by 27
- 2021Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuationcited by 16
- 2021Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inferencecited by 10
- 2023CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inferencecited by 10
- 2023Selective Inference for Changepoint detection by Recurrent Neural Networkcited by 4
- 2025LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgradescited by 4
- 2024Statistical Test for Auto Feature Engineering by Selective Inferencecited by 3
- 2025Statistical Inference for Autoencoder-based Anomaly Detection after Representation Learning-based Domain Adaptationcited by 2
- 2023Bounded P-values in Parametric Programming-based Selective Inferencecited by 1
- 2021Few-shot Learning for Unsupervised Feature Selectioncited by 0
- 2022Neural Networks beyond explainability: Selective inference for sequence motifscited by 0
- 2025Statistical Inference for Clustering-based Anomaly Detectioncited by 0
- 2026Statistical Testing for Multiple Instance Learning via Selective Inference with Applications to Computational Pathology21 Sep 2026
- 2025Statistical Inference for Autoencoder-based Anomaly Detection after Representation Learning-based Domain Adaptation9 Aug 2025
- 2025LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades17 May 2025
- 2025Statistical Inference for Clustering-based Anomaly Detection25 Apr 2025
- 2024Statistical Test for Auto Feature Engineering by Selective Inference13 Oct 2024
- 2023Selective Inference for Changepoint detection by Recurrent Neural Network25 Nov 2023
- 2023CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference23 Oct 2023
- 2023Bounded P-values in Parametric Programming-based Selective Inference21 Jul 2023
- 2022Neural Networks beyond explainability: Selective inference for sequence motifs23 Dec 2022
- 2022Efficient Aggregated Kernel Tests using Incomplete U-statistics18 Jun 2022
- 2021Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference18 Oct 2021
- 2021Few-shot Learning for Unsupervised Feature Selection2 Jul 2021
- 2022Efficient Aggregated Kernel Tests using Incomplete U-statisticscited by 27
- 2021Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuationcited by 16
- 2021Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inferencecited by 10
- 2023CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inferencecited by 10
- 2023Selective Inference for Changepoint detection by Recurrent Neural Networkcited by 4
- 2025LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgradescited by 4
- 2024Statistical Test for Auto Feature Engineering by Selective Inferencecited by 3
- 2025Statistical Inference for Autoencoder-based Anomaly Detection after Representation Learning-based Domain Adaptationcited by 2
- 2023Bounded P-values in Parametric Programming-based Selective Inferencecited by 1
- 2021Few-shot Learning for Unsupervised Feature Selectioncited by 0
- 2022Neural Networks beyond explainability: Selective inference for sequence motifscited by 0
- 2025Statistical Inference for Clustering-based Anomaly Detectioncited by 0
12 most cited of 13 All 13 (JSON)
- 2026Statistical Testing for Multiple Instance Learning via Selective Inference with Applications to Computational Pathology21 Sep 2026
- 2025Statistical Inference for Autoencoder-based Anomaly Detection after Representation Learning-based Domain Adaptation9 Aug 2025
- 2025LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades17 May 2025
- 2025Statistical Inference for Clustering-based Anomaly Detection25 Apr 2025
- 2024Statistical Test for Auto Feature Engineering by Selective Inference13 Oct 2024
- 2023Selective Inference for Changepoint detection by Recurrent Neural Network25 Nov 2023
- 2023CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference23 Oct 2023
- 2023Bounded P-values in Parametric Programming-based Selective Inference21 Jul 2023
- 2022Neural Networks beyond explainability: Selective inference for sequence motifs23 Dec 2022
- 2022Efficient Aggregated Kernel Tests using Incomplete U-statistics18 Jun 2022
- 2021Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference18 Oct 2021
- 2021Few-shot Learning for Unsupervised Feature Selection2 Jul 2021
12 newest of 13 All 13 (JSON)