The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Random classification noise defeats all convex potential boosters
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Cites
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
Friedman, J., Hastie, T., & Tibshirani, R. (2000) · The Annals of Statistics · doi:10.1214/aos/1016218223 · Cited by 6,884
Boosting a Weak Learning Algorithm by Majority
Freund, Y. (1995) · Information and Computation · doi:10.1006/inco.1995.1136 · Cited by 1,674
Cited by
Foundations of Machine Learning
Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2018) · doi:10.7551/mitpress/10290.001.0001 · Cited by 1,122
Schapire, R. E. (2013) · Empirical Inference · doi:10.1007/978-3-642-41136-6_5 · Cited by 1,013
A Survey of Text Classification Algorithms
Aggarwal, C. C., & Zhai, C. (2012) · Mining Text Data · doi:10.1007/978-1-4614-3223-4_6 · Cited by 842
Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis
Karimi, D., Dou, H., Warfield, S. K., & Gholipour, A. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101759 · Cited by 706
Genomic Selection in Plant Breeding: A Comparison of Models
Heslot, N., Yang, H., Sorrells, M. E., & Jannink, J. (2012) · Crop Science · doi:10.2135/cropsci2011.06.0297 · Cited by 698
Metadata
- Authors
- Long, P. M., & Servedio, R. A.
- Venue
- Machine Learning
- Published
- 2009-12-22
- Volume
- 78
- Issue
- 3
- Pages
- 287-304
- ISSN
- 0885-6125 (ISSN-L)
- 1573-0565
- OpenAlex
- W2490901831
- Cited by
- 171
- References
- 3
- FWCI
- 5.78
- Type
- journal article
- Language
- en
- Open access
- bronze
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- The paper
- Long, P. M., & Servedio, R. A. (2010). Random classification noise defeats all convex potential boosters. Machine Learning. https://doi.org/10.1007/s10994-009-5165-z
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.
