Trimmed Density Ratio Estimation
Not on the map. Why?
Abstract (arXiv)
Density ratio estimation is a vital tool in both machine learning and statistical community. However, due to the unbounded nature of density ratio, the estimation procedure can be vulnerable to corrupted data points, which often pushes the estimated ratio toward infinity. In this paper, we present a robust estimator which automatically identifies and trims outliers. The proposed estimator has a convex formulation, and the global optimum can be obtained via subgradient descent. We analyze the parameter estimation error of this estimator under high-dimensional settings. Experiments are conducted to verify the effectiveness of the estimator.
Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Mar 2017.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 4; 2022: 1; 2023: 2; 2024: 2; 2025: 2; 2026: 4.
15 papers.
Sort:
By area:
- 2021Mandoline: Model Evaluation under Distribution Shiftcited by 55
- 2024A Short Survey on Importance Weighting for Machine Learningcited by 15
- 2023Multiply Robust Federated Estimation of Targeted Average Treatment Effectscited by 13
- 2021Meta-Learning for Relative Density-Ratio Estimationcited by 6
- 2021A Unified Framework for Multi-distribution Density Ratio Estimationcited by 5
- 2024General Frameworks for Conditional Two-Sample Testingcited by 3
- 2025Diffusion Secant Alignment for Score-Based Density Ratio Estimationcited by 3
- 2026A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimationcited by 3
- 2021Estimation of Local Average Treatment Effect by Data Combinationcited by 2
- 2023Density Ratio Estimation and Neyman Pearson Classification with Missing Datacited by 2
- 2026Weight Clipping for Robust Conformal Inference under Unbounded Covariate Shiftscited by 2
- 2022Unsupervised Change Detection using DRE-CUSUMcited by 1
- 2026Weight Clipping for Robust Conformal Inference under Unbounded Covariate Shifts3 May 2026
- 2026Towards Disentangled Preference Optimization Dynamics: Suppress the Loser, Preserve the Winner20 Apr 2026
- 2026One-Step Score-Based Density Ratio Estimation12 Apr 2026
- 2026A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimation31 Jan 2026
- 2025Robust and Sparse Estimation of Unbounded Density Ratio under Heavy Contamination10 Dec 2025
- 2025Diffusion Secant Alignment for Score-Based Density Ratio Estimation5 Sep 2025
- 2024General Frameworks for Conditional Two-Sample Testing22 Oct 2024
- 2024A Short Survey on Importance Weighting for Machine Learning15 Mar 2024
- 2023Multiply Robust Federated Estimation of Targeted Average Treatment Effects22 Sep 2023
- 2023Density Ratio Estimation and Neyman Pearson Classification with Missing Data21 Feb 2023
- 2022Unsupervised Change Detection using DRE-CUSUM27 Jan 2022
- 2021A Unified Framework for Multi-distribution Density Ratio Estimation7 Dec 2021
3 more
- 2021Estimation of Local Average Treatment Effect by Data Combination11 Sep 2021
- 2021Meta-Learning for Relative Density-Ratio Estimation2 Jul 2021
- 2021Mandoline: Model Evaluation under Distribution Shift1 Jul 2021
- 2021Mandoline: Model Evaluation under Distribution Shiftcited by 55
- 2024A Short Survey on Importance Weighting for Machine Learningcited by 15
- 2023Multiply Robust Federated Estimation of Targeted Average Treatment Effectscited by 13
- 2021Meta-Learning for Relative Density-Ratio Estimationcited by 6
- 2021A Unified Framework for Multi-distribution Density Ratio Estimationcited by 5
- 2024General Frameworks for Conditional Two-Sample Testingcited by 3
- 2025Diffusion Secant Alignment for Score-Based Density Ratio Estimationcited by 3
- 2026A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimationcited by 3
- 2021Estimation of Local Average Treatment Effect by Data Combinationcited by 2
- 2023Density Ratio Estimation and Neyman Pearson Classification with Missing Datacited by 2
- 2026Weight Clipping for Robust Conformal Inference under Unbounded Covariate Shiftscited by 2
- 2022Unsupervised Change Detection using DRE-CUSUMcited by 1
12 most cited of 14 All 14 (JSON)
- 2026Weight Clipping for Robust Conformal Inference under Unbounded Covariate Shifts3 May 2026
- 2026One-Step Score-Based Density Ratio Estimation12 Apr 2026
- 2026A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimation31 Jan 2026
- 2025Robust and Sparse Estimation of Unbounded Density Ratio under Heavy Contamination10 Dec 2025
- 2025Diffusion Secant Alignment for Score-Based Density Ratio Estimation5 Sep 2025
- 2024General Frameworks for Conditional Two-Sample Testing22 Oct 2024
- 2024A Short Survey on Importance Weighting for Machine Learning15 Mar 2024
- 2023Multiply Robust Federated Estimation of Targeted Average Treatment Effects22 Sep 2023
- 2023Density Ratio Estimation and Neyman Pearson Classification with Missing Data21 Feb 2023
- 2022Unsupervised Change Detection using DRE-CUSUM27 Jan 2022
- 2021A Unified Framework for Multi-distribution Density Ratio Estimation7 Dec 2021
- 2021Estimation of Local Average Treatment Effect by Data Combination11 Sep 2021
12 newest of 14 All 14 (JSON)