The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Risk bounds for model selection via penalization
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Citations
Cites
Estimating the Dimension of a Model
Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
Information Theory and an Extension of the Maximum Likelihood Principle
Akaike, H. (1998) · Springer Series in Statistics · doi:10.1007/978-1-4612-1694-0_15 · Cited by 17,781
Ideal spatial adaptation by wavelet shrinkage
Donoho, D. L., & Johnstone, I. M. (1994) · Biometrika · doi:10.1093/biomet/81.3.425 · Cited by 8,760
Multivariate Adaptive Regression Splines
Friedman, J. H. (1991) · The Annals of Statistics · doi:10.1214/aos/1176347963 · Cited by 8,000
Whittaker, E. T., & Watson, G. N. (2021) · Cambridge University Press eBooks · doi:10.1017/9781009004091 · Cited by 6,850
Modeling by shortest data description
Rissanen, J. (1978) · Automatica · doi:10.1016/0005-1098(78)90005-5 · Cited by 6,011
Information Theory and Reliable Communication.
Lee, P. M., & Gallager, R. T. (1970) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344305 · Cited by 5,399
Introduction to Fourier Analysis on Euclidean Spaces.
Stein, E. M., & Weiss, G. (1971) · Cited by 5,080
Spline Models for Observational Data.
Muller, H.-G., & Wahba, G. (1991) · Journal of the American Statistical Association · doi:10.2307/2290434 · Cited by 4,928
(1967) · Project Euclid (Cornell University) · Cited by 4,720
Cited by
A survey of cross-validation procedures for model selection
Arlot, S., & Celisse, A. (2010) · Statistics Surveys · doi:10.1214/09-ss054 · Cited by 3,522
Challenges of Big Data analysis
Fan, J., Han, F., & Liu, H. (2014) · National Science Review · doi:10.1093/nsr/nwt032 · Cited by 1,482
Concentration Inequalities and Model Selection
(2007) · Lecture Notes in Mathematics · doi:10.1007/978-3-540-48503-2 · Cited by 744
Self-citationRegularization of Wavelet Approximations
Antoniadis, A., & Fan, J. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753208942 · Cited by 498
Empirical Margin Distributions and Bounding the Generalization Error of Combined Classifiers
Koltchinskii, V., & Panchenko, D. (2002) · The Annals of Statistics · doi:10.1214/aos/1015362183 · Cited by 451
Metadata
- Authors
- Barron, A., Birgé, L., & Massart, P.
- Venue
- Probability Theory and Related Fields
- Published
- 1999-02
- Volume
- 113
- Issue
- 3
- Pages
- 301-413
- ISSN
- 0178-8051 (ISSN-L)
- 1432-2064
- OpenAlex
- W1996268356
- Cited by
- 657
- References
- 73
- FWCI
- 26.51
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
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- CoChat. (2026). Citation check: Risk bounds for model selection via penalization. https://app.cochat.ai/papers/10.1007/s004400050210
- The paper
- Barron, A., Birgé, L., & Massart, P. (1999). Risk bounds for model selection via penalization. Probability Theory and Related Fields. https://doi.org/10.1007/s004400050210
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
