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» Semi-Supervised Support Vector Machines
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128
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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 3 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
161
Voted
MOBISYS
2008
ACM
16 years 2 months ago
Behavioral detection of malware on mobile handsets
A novel behavioral detection framework is proposed to detect mobile worms, viruses and Trojans, instead of the signature-based solutions currently available for use in mobile devi...
Abhijit Bose, Xin Hu, Kang G. Shin, Taejoon Park
124
Voted
IUI
2006
ACM
15 years 8 months ago
A hybrid learning system for recognizing user tasks from desktop activities and email messages
The TaskTracer system seeks to help multi-tasking users manage the resources that they create and access while carrying out their work activities. It does this by associating with...
Jianqiang Shen, Lida Li, Thomas G. Dietterich, Jon...
118
Voted
BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
15 years 6 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
139
Voted
SIGIR
2010
ACM
15 years 6 months ago
Effective music tagging through advanced statistical modeling
Music information retrieval (MIR) holds great promise as a technology for managing large music archives. One of the key components of MIR that has been actively researched into is...
Jialie Shen, Wang Meng, Shuichang Yan, HweeHwa Pan...