Algorithmic Learning in a Random World
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Registry
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Split conformal prediction provides statistically valid prediction sets or intervals under minimal assumptions.
“Conformal Prediction (CP) is a model-agnostic, distributionfree framework for uncertainty quantification that provides statistically valid prediction sets or intervals, for classification and regression tasks respectively, under minimal assumptions [6], [7].”
From ConfIC-RCA: Statistically Grounded Efficient Estimation of Segmentation Quality (2025) · cites this paper as [6]
The procedure guarantees that at a user-chosen confidence level 1-α, the inner mask contains at most a user-specified fraction τ of false-positive pixels.
“Our procedure, based on inductive (or 'split') Conformal Prediction (CP) [21, 15], guarantees that at a user-chosen confidence level 1 -α , the inner mask contains at most a userspecified fraction τ of false-positive pixels.”
From Controlling False Positives in Image Segmentation via Conformal Prediction (2025) · cites this paper as [21]
The citation lists haven’t been fetched yet
Cited by 296
- Authors
- Vovk, V., Gammerman, A., & Shafer, G.
- Affiliations
- Royal Holloway University of London (GB)
- Rutgers, The State University of New Jersey (US)
- Venue
- Springer eBooks
- Publisher
- Springer International Publishing
- Published
- 2022
- OpenAlex
- W4312294904
- Cited by
- 296
- References
- 0
- Citations by year
- 2026: 63 · 2025: 79 · 2024: 47 · 2023: 33 · 2022: 20 · 2021: 6 · 2020: 6 · 2019: 5 · 2018: 4 · 2017: 2 · 2016: 4 · 2015: 3 · 2014: 7 · 2013: 7 · 2012: 5
- FWCI
- 29.33
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- conformal prediction, algorithmic learning, prediction intervals, uncertainty estimation, nonparametric prediction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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