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» Chunking with Support Vector Machines
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IPM
2008
100views more  IPM 2008»
13 years 9 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
JMLR
2006
132views more  JMLR 2006»
13 years 9 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof
BMCBI
2004
140views more  BMCBI 2004»
13 years 9 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard
BMCBI
2004
123views more  BMCBI 2004»
13 years 9 months ago
Interaction profile-based protein classification of death domain
Background: The increasing number of protein sequences and 3D structure obtained from genomic initiatives is leading many of us to focus on proteomics, and to dedicate our experim...
Drew Lett, Michael Hsing, Frederic Pio
IJDAR
2010
110views more  IJDAR 2010»
13 years 7 months ago
Locating and parsing bibliographic references in HTML medical articles
The set of references that typically appear toward the end of journal articles is sometimes, though not always, a field in bibliographic (citation) databases. But even if referenc...
Jie Zou, Daniel X. Le, George R. Thoma