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» Relation Extraction Using Support Vector Machine
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NSDI
2008
13 years 11 months ago
Designing and Implementing Malicious Hardware
Hidden malicious circuits provide an attacker with a stealthy attack vector. As they occupy a layer below the entire software stack, malicious circuits can bypass traditional defe...
Samuel T. King, Joseph Tucek, Anthony Cozzie, Chri...
NIPS
2003
13 years 10 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
BMCBI
2010
97views more  BMCBI 2010»
13 years 9 months ago
SeqRate: sequence-based protein folding type classification and rates prediction
Background: Protein folding rate is an important property of a protein. Predicting protein folding rate is useful for understanding protein folding process and guiding protein des...
Guan Ning Lin, Zheng Wang, Dong Xu, Jianlin Cheng
BMCBI
2008
228views more  BMCBI 2008»
13 years 9 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
JMLR
2002
137views more  JMLR 2002»
13 years 8 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller