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Online Conformal Prediction for Non-Exchangeable Panel Data

arXiv 2605.17705 ↗First posted 18 May 2026stat.ML cs.LG stat.MEcited by 0

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Abstract (arXiv)

We study online conformal prediction in a partially observed panel: a new cross-section of peer outcomes is observed before each target outcome, target feedback may be intermittent or absent, and neither units nor rounds need be exchangeable. We propose Weighted Temporal Quantile Adjustment (W-TQA), which combines similarity weights learned from unit histories with an adaptive target-specific miscoverage level. We prove that neither target-peer mismatch nor coverage on unrevealed rounds is identifiable, so assumptions on cross-unit similarity and on the feedback mechanism cannot be avoided. We bound the past-conditional miscoverage in terms of this mismatch, quantify the cost of learning the weights under a profile-similarity assumption, and show that the implemented procedure, which falls back on the largest peer score, attains long-run average coverage under missing-completely-at-random feedback and a feasibility condition on the calibration panel. On synthetic panels and four real panels, including a genuinely asynchronous U.S.-to-Tokyo equity panel, W-TQA attains the highest coverage on the worst-covered target units on every panel; similarity weighting contributes most when target feedback is scarce, and temporal adaptation more as feedback accumulates.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 26 of its 48 references that are in the map. First posted on arXiv 18 May 2026.

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26 of 48 references.

References · 26

  1. 2016Distribution-Free Predictive Inference For Regressioncited by 668
  2. 2019Conformal Prediction Under Covariate Shiftcited by 519
  3. 2021Adaptive Conformal Inference Under Distribution Shiftcited by 375
  4. 2022Conformal prediction beyond exchangeabilitycited by 355
  5. 2022Adaptive Conformal Predictions for Time Seriescited by 161
  6. 2022Conformal Inference for Online Prediction with Arbitrary Distribution Shiftscited by 128
  7. 2021Localized Conformal Prediction: A Generalized Inference Framework for Conformal Predictioncited by 114
  8. 2021Distribution-free uncertainty quantification for classification under label shiftcited by 101
  9. 2023Conformal PID Control for Time Series Predictioncited by 88
  10. 2023Improved Online Conformal Prediction via Strongly Adaptive Online Learningcited by 78
  11. 2022Sequential Predictive Conformal Inference for Time Seriescited by 75
  12. 2024Online conformal prediction with decaying step sizescited by 56
14 more
  1. 2020Conformal prediction for time seriescited by 53
  2. 2023Conformal prediction with local weights: randomization enables local guaranteescited by 48
  3. 2023Conformal Prediction for Time Series with Modern Hopfield Networkscited by 42
  4. 2018Distribution-Free Prediction Sets for Two-Layer Hierarchical Modelscited by 35
  5. 2023Non-Exchangeable Conformal Risk Controlcited by 29
  6. 2022Conformal Prediction with Temporal Quantile Adjustmentscited by 25
  7. 2024Kernel-based Optimally Weighted Conformal Time-Series Predictioncited by 15
  8. 2024Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedbackcited by 11
  9. 2024Stochastic Online Conformal Prediction with Semi-Bandit Feedbackcited by 8
  10. 2025Mirror Online Conformal Prediction with Intermittent Feedbackcited by 7
  11. 2026Online Conformal Prediction with Adversarial Semi-bandit Feedback via Regret Minimizationcited by 4
  12. 2023Conformal Predictions for Longitudinal Datacited by 3
  13. 2021Multi-Sensor Data Fusion for Accurate Traffic Speed and Travel Time Reconstructioncited by 1
  14. 2026Online Localized Conformal Predictioncited by 1

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