mlsanityData to 14 Oct 2026

Exact post-selection inference, with application to the lasso

arXiv 1311.6238 ↗First posted 25 Nov 2013math.ST stat.ME stat.MLcited by 91

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Abstract (arXiv)

We develop a general approach to valid inference after model selection. At the core of our framework is a result that characterizes the distribution of a post-selection estimator conditioned on the selection event. We specialize the approach to model selection by the lasso to form valid confidence intervals for the selected coefficients and test whether all relevant variables have been included in the model.

Key facts. Cited by 91 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Nov 2013.

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Citing papers per year: 2021: 14; 2022: 15; 2023: 16; 2024: 11; 2025: 16; 2026: 19.

91 papers.

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  1. 2021MMD Aggregated Two-Sample Testcited by 75
  2. 2022Efficient Aggregated Kernel Tests using Incomplete U-statisticscited by 27
  3. 2021More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programmingcited by 25
  4. 2022Selective inference for k-means clusteringcited by 22
  5. 2021Sampling with Mirrored Stein Operatorscited by 17
  6. 2023Valid P-Value for Deep Learning-Driven Salient Regioncited by 17
  7. 2021Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuationcited by 16
  8. 2021Fast and More Powerful Selective Inference for Sparse High-order Interaction Modelcited by 15
  9. 2021Tree-Values: selective inference for regression treescited by 15
  10. 2021Data fission: splitting a single data pointcited by 14
  11. 2024Confidence on the Focal: Conformal Prediction with Selection-Conditional Coveragecited by 14
  12. 2023DRCFS: Doubly Robust Causal Feature Selectioncited by 12
38 more
  1. 2021The Terminating-Random Experiments Selector: Fast High-Dimensional Variable Selection with False Discovery Rate Controlcited by 10
  2. 2021Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inferencecited by 10
  3. 2022Valid Inference After Causal Discoverycited by 10
  4. 2023CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inferencecited by 10
  5. 2025PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Frameworkcited by 9
  6. 2023Generalized Data Thinning Using Sufficient Statisticscited by 8
  7. 2021Exact Statistical Inference for the Wasserstein Distance by Selective Inferencecited by 7
  8. 2023Adaptive debiased machine learning using data-driven model selection techniquescited by 7
  9. 2024Statistical Test for Anomaly Detections by Variational Auto-Encoderscited by 7
  10. 2024A Flexible Defense Against the Winner's Cursecited by 7
  11. 2026Towards Reliable LLM Evaluation: Correcting the Winner's Curse in Adaptive Benchmarkingcited by 7
  12. 2023On the hierarchical Bayesian modelling of frequency response functionscited by 6
  13. 2024Statistical Test for Attention Map in Vision Transformercited by 6
  14. 2025DUAL: Learning Diverse Kernels for Aggregated Two-sample and Independence Testingcited by 6
  15. 2023Selective Inference for Changepoint detection by Recurrent Neural Networkcited by 4
  16. 2023Learning Rate Free Sampling in Constrained Domainscited by 3
  17. 2024Statistical Test for Feature Selection Pipelines by Selective Inferencecited by 3
  18. 2024Statistical Test for Auto Feature Engineering by Selective Inferencecited by 3
  19. 2025Quantifying Statistical Significance of Deep Nearest Neighbor Anomaly Detection via Selective Inferencecited by 3
  20. 2022Holistic Generalized Linear Modelscited by 2
  21. 2023Meta-models for transfer learning in source localisationcited by 2
  22. 2024Statistical Inference for Feature Selection after Optimal Transport-based Domain Adaptationcited by 2
  23. 2024Controllable RANSAC-based Anomaly Detection via Hypothesis Testingcited by 2
  24. 2025Change Point Detection in the Frequency Domain with Statistical Reliabilitycited by 2
  25. 2025Powerful rank verification for multivariate Gaussian data with any covariance structurecited by 2
  26. 2025Online Selective Conformal Prediction: Errors and Solutionscited by 2
  27. 2025Statistical Inference for Autoencoder-based Anomaly Detection after Representation Learning-based Domain Adaptationcited by 2
  28. 2026Data-driven sparse identification of governing PDEs via knockoff filters and multi-criteria trade-offscited by 2
  29. 2021Spatially relaxed inference on high-dimensional linear modelscited by 1
  30. 2021Inference for High Dimensional Censored Quantile Regressioncited by 1
  31. 2022Black-box Selective Inference via Bootstrappingcited by 1
  32. 2022A Confidence Machine for Sparse High-Order Interaction Modelcited by 1
  33. 2022Multi-Study Boosting: Theoretical Considerations for Merging vs. Ensemblingcited by 1
  34. 2022Two-Stage Robust and Sparse Distributed Statistical Inference for Large-Scale Datacited by 1
  35. 2023Bounded P-values in Parametric Programming-based Selective Inferencecited by 1
  36. 2024Discovering Significant Topics from Legal Decisions with Selective Inferencecited by 1
  37. 2024Statistical Test for Diffusion-Based Anomaly Localization via Selective Inferencecited by 1
  38. 2024U-learning for Prediction Inference via Combinatory Multi-Subsampling: With Applications to LASSO and Neural Networkscited by 1

50 most cited of 91 All 91 (JSON)