Conditional validity of inductive conformal predictors
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
The algorithm presented herein differs from previous high-probability risk control work: it has a guarantee in expectation, and neither the algorithm nor its analysis share much technical similarity with these previous works.
“the algorithm presented herein differs greatly: it has a guarantee in expectation, and neither the algorithm nor its analysis share much technical similarity with these previous works.”
From Conformal Risk Control (2022) · cites this paper as [17]
Cites
Greedy function approximation: A gradient boosting machine
Friedman, J. H. (2001) · The Annals of Statistics · doi:10.1214/aos/1013203451 · Cited by 30,731 · see citing works
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970 · see citing works
A decision-theoretic generalization of on-line learning and an application to boosting
Freund, Y., & Schapire, R. E. (1997) · Journal of Computer and System Sciences · doi:10.1006/jcss.1997.1504 · Cited by 20,466 · see citing works
Inductive Confidence Machines for Regression
Papadopoulos, H., Proedrou, K., Vovk, V., & Gammerman, A. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-36755-1_29 · Cited by 346 · see citing works
Self-citation
Flagged first, then by citations
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Distribution-free, Risk-controlling Prediction Sets
Bates, S., Angelopoulos, A., Lei, L., Malik, J., & Jordan, M. (2021) · Journal of the ACM · doi:10.1145/3478535 · Cited by 144 · see citing works
Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data
Chernozhukov, V., Wüthrich, K., & Zhu, Y. (2018) · doi:10.1920/wp.cem.2018.1618 · Cited by 57 · see citing works
Angelopoulos, A. N., Bates, S., Fisch, A., Lei, L., & Schuster, T. (2022) · arXiv · doi:10.48550/arxiv.2208.02814 · Cited by 37 · see citing works
Angelopoulos, A. N., Bates, S., Zrnic, T., & Jordan, M. I. (2022) · Harvard Data Science Review · doi:10.1162/99608f92.16c71dad · Cited by 8 · see citing works
When Average Calibration Fails: Site-Conditional Federated Conformal Risk Control
Shahid, N. F. (2026) · arXiv · doi:10.48550/arxiv.2606.20115
- Authors
- Vovk, V.
- Affiliations
- Royal Holloway University of London (GB)
- Corresponding author
- Vovk, Vladimir
- ORCID
- Vovk, Vladimir
- Venue
- Machine Learning
- Published
- 2013-05-08
- Volume
- 92
- Issue
- 2-3
- Pages
- 349-376
- ISSN
- 0885-6125 (ISSN-L)
- 1573-0565
- OpenAlex
- W2166693382
- Cited by
- 225
- References
- 4
- Citations by year
- 2026: 41 · 2025: 31 · 2024: 41 · 2023: 28 · 2022: 10 · 2021: 22 · 2020: 11 · 2019: 10 · 2018: 8 · 2017: 6 · 2016: 3 · 2015: 1 · 2014: 8 · 2013: 5
- FWCI
- 5.86
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Machine Learning (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Asian Conference on Machine Learning
- Funders
- Research Promotion Foundation
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
- Keywords
- coverage probability, set prediction, ROC curve, prediction intervals
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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