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Predicting Structured Objects with Support Vector Machines

delete2009-11-01
delete67
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OA
AI
T
Thorsten Joachims *
T
Thomas Hofmann
Y
Yisong Yue
C
Chun-Nam Yu
DOI:10.1145/1592761.1592783delete
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摘要

摘要

En 中文
Machine Learning today offers a broad repertoire of methods for classification and regression. But what if we need to predict complex objects like trees, orderings, or alignments? Such problems arise naturally in natural language processing, search engines, and bioinformatics. The following explores a generalization of Support Vector Machines (SVMs) for such complex prediction problems.
Keyword:
PROTEIN-STRUCTURE ALIGNMENT
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期刊

Communications of the ACM 封面图
Communications of the ACM
IF:
12.2
论文数:
1.2W
被引数:
3.7W

机构

C
Cornell University
学者数:
6.3W
论文数: 5.4W
被引数: 10.9W
G
Google Incorporated
学者数:
3.5K
论文数: 1.8K
被引数: 8
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