mlsanityData to 14 Oct 2026

Uncertainty Quantification With Multiple Sources

arXiv 2405.06479 ↗First posted 10 May 2024stat.ME stat.MLcited by 2

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Abstract (arXiv)

Weighted conformal prediction (WCP) has been commonly used to quantify prediction uncertainty under covariate shift. However, the effectiveness of WCP relies heavily on the degree of overlap between the training and test covariate distributions. This challenge is exacerbated in multi-source settings with varying covariate distributions, where direct application of WCP can be impractical. In this paper, we address the multi-source setup by leveraging WCP under the assumption of a shared conditional distribution. We investigate two extensions of WCP: (i) a merge-based aggregation of source-specific weighted conformal prediction sets, and (ii) a data-pooling strategy that jointly reweights samples across all sources. Theoretical guarantees are provided for the proposed approaches, and experiments are conducted based on a synthetic regression task and a multi-domain image classification benchmark to validate our proposed methods.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 18 of its 37 references that are in the map. First posted on arXiv 10 May 2024.

Builds on

18 of 37 references.

References · 18

  1. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,049
  2. 2014Unsupervised Domain Adaptation by Backpropagationcited by 1,917
  3. 2019Conformal Prediction Under Covariate Shiftcited by 519
  4. 2022Conformal Risk Controlcited by 299
  5. 2023Conformal Prediction With Conditional Guaranteescited by 152
  6. 2020Conformal Inference of Counterfactuals and Individual Treatment Effectscited by 151
  7. 2021Localized Conformal Prediction: A Generalized Inference Framework for Conformal Predictioncited by 114
  8. 2022Conformal Prediction Under Feedback Covariate Shift for Biomolecular Designcited by 54
  9. 2021Conformalized Survival Analysiscited by 53
  10. 2023Conformal prediction with local weights: randomization enables local guaranteescited by 48
  11. 2018Distribution-Free Prediction Sets for Two-Layer Hierarchical Modelscited by 35
  12. 2024Merging uncertainty sets via majority votecited by 30
6 more
  1. 2023Model-free selective inference under covariate shift via weighted conformal p-valuescited by 29
  2. 2021Multi Split Conformal Predictioncited by 21
  3. 2023Distribution-free inference with hierarchical datacited by 15
  4. 2024Group-Weighted Conformal Predictioncited by 14
  5. 2023SymmPI: Predictive Inference for Data with Group Symmetriescited by 8
  6. 2024Predictive Inference in Multi-environment Scenarioscited by 4

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Cited by year

Citing papers per year: 2024: 2.

2 papers.

  1. 2024Conformal Prediction: A Data Perspectivecited by 25
  2. 2024Distribution-Free Predictive Inference under Unknown Temporal Driftcited by 0