The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Fast Kernels for String and Tree Matching
Abstract
In this paper we present a new algorithm suitable for matching discrete objects such as strings and trees in linear time, thus obviating dynamic programming with quadratic time complexity. Furthermore, prediction cost in many cases can be reduced to linear cost in the length of the se-quence to be classified, regardless of the number of support vectors. This improvement on the currently available algorithms makes string kernels a viable alternative for the practitioner. 1
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Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
Text Mining Infrastructure in R
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Mismatch string kernels for discriminative protein classification
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Authorship Attribution for Social Media Forensics
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On Authorship Attribution via Markov Chains and Sequence Kernels
Sanderson, C., & Guenter, S. (2006) · 18th International Conference on Pattern Recognition (ICPR'06) · doi:10.1109/icpr.2006.899 · Cited by 15
Metadata
- Authors
- Vishwanathan, S. V. N., & Smola, A. J.
- Venue
- Kernel Methods in Computational Biology
- Publisher
- The MIT Press
- Published
- 2004-07-16
- Pages
- 113-130
- OpenAlex
- W2124225821
- Cited by
- 294
- References
- 20
- FWCI
- 38.94
- Type
- book chapter
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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