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Cited by 3,298

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Selection of relevant features and examples in machine learning

Open access
Blum, Avrim L., Langley, Pat·1997·Artificial Intelligence
DOI 10.1016/s0004-3702(97)00063-5
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Cites

Show all 5 references

Research works printed but not linked: 31

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  3. Baluja, 1997, Dynamic relevance: vision-based focus of attention using artificial neural networks (Technical Note), Artificial Intelligence, 97, 381, 10.1016/S0004-3702(97)00065-9 · DOI
  4. Blum, 1992, Learning Boolean functions in an infinite attribute space, Machine Learning, 9, 373, 10.1007/BF00994112 · DOI
  5. Blum, 1995, Learning in the presence of finitely or infinitely many irrelevant attributes, J. Comput. System Sci., 50, 32, 10.1006/jcss.1995.1004 · DOI
  6. Blumer, 1987, Occam's razor, Inform. Process. Lett., 24, 377, 10.1016/0020-0190(87)90114-1 · DOI · Paper page
  7. Blumer, 1989, Learnability and the Vapnik-Chervonenkis dimension, J. ACM, 36, 929, 10.1145/76359.76371 · DOI · Paper page
  8. Clark, 1989, The CN2 induction algorithm, Machine Learning, 3, 261, 10.1007/BF00116835 · DOI · Paper page
  9. Cohn, 1996, Active learning with statistical models, J. Artif. Intell. Research, 4, 129, 10.1613/jair.295 · DOI · Paper page
  10. Comon, 1994, Independent component analysis: a new concept, Signal Process., 36, 287, 10.1016/0165-1684(94)90029-9 · DOI · Paper page
  11. Cover, 1967, Nearest neighbor pattern classification, IEEE Trans. Inform. Theory, 13, 21, 10.1109/TIT.1967.1053964 · DOI · Paper page
  12. Daelemans, 1994, The acquisition of stress: a data-oriented approach, Comput. Linguistics, 20, 421
  13. Drucker, 1992, Improving performance in neural networks using a boosting algorithm, Vol. 4
  14. Greiner, 1997, Knowing what doesn't matter: exploiting the omission of irrelevant data, Artificial Intelligence, 97, 345, 10.1016/S0004-3702(97)00048-9 · DOI
  15. Holte, 1993, Very simple classification rules perform well on most commonly used domains, Machine Learning, 11, 63, 10.1023/A:1022631118932 · DOI · Paper page
  16. Johnson, 1974, Approximation algorithms for combinatorial problems, J. Comput. System Sci., 9, 256, 10.1016/S0022-0000(74)80044-9 · DOI · Paper page
  17. Kivinen, 1997, The Perceptron algorithm versus Winnow: linear versus logarithmic mistake bounds when few input variables are relevant (Technical Note), Artificial Intelligence, 97, 325, 10.1016/S0004-3702(97)00039-8 · DOI
  18. Kohavi, 1997, Wrappers for feature subset selection, Artificial Intelligence, 97, 273, 10.1016/S0004-3702(97)00043-X · DOI · Paper page
  19. Knobe, 1977, A method for inferring context-free grammars, Inform. and Control, 31, 129, 10.1016/S0019-9958(76)80003-4 · DOI
  20. Langley, 1997, Scaling to domains with many irrelevant features, Vol. 4
  21. Littlestone, 1988, Learning quickly when irrelevant attributes abound: a new linear threshold algorithm, Machine Learning, 2, 285, 10.1007/BF00116827 · DOI · Paper page
  22. Littlestone, 1997, An apobayesian relative of winnow, Vol. 9
  23. Littlestone, 1994, The weighted majority algorithm, Inform. and Comput., 108, 212, 10.1006/inco.1994.1009 · DOI · Paper page
  24. Michalski, 1980, Pattern recognition as rule-guided inductive inference, IEEE Trans. Pattern Anal. Machine Intell., 2, 349, 10.1109/TPAMI.1980.4767034 · DOI
  25. Mitchell, 1982, Generalization as search, Artificial Intelligence, 18, 203, 10.1016/0004-3702(82)90040-6 · DOI · Paper page
  26. Pazzani, 1992, A framework for the average case analysis of conjunctive learning algorithms, Machine Learning, 9, 349, 10.1007/BF00994111 · DOI
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  28. Rivest, 1993, Inference of finite automata using homing sequences, Inform. and Comput., 103, 299, 10.1006/inco.1993.1021 · DOI
  29. Rumelhart, 1986, Learning internal representations by error propagation, Vol. 1
  30. Sammut, 1986, Learning concepts by asking questions, Vol. 2
  31. Sinclair, 1989, Approximate counting, uniform generation and rapidly mixing Markov chains, Inform. and Comput., 82, 93, 10.1016/0890-5401(89)90067-9 · DOI · Paper page

Cited by

Metadata

Authors
Blum, A. L., & Langley, P.
Venue
Artificial Intelligence
Publisher
Elsevier BV
Published
1997-12
Volume
97
Issue
1-2
Pages
245-271
ISSN
0004-3702 (ISSN-L)
DOI
10.1016/s0004-3702(97)00063-5
OpenAlex
W2040884411
Cited by
3,298
References
5
FWCI
24.73
Type
journal article
Language
en
Open access
bronze
Licence

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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.