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» Using Machine Learning to Focus Iterative Optimization
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94
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ICML
2003
IEEE
16 years 3 months ago
Adaptive Overrelaxed Bound Optimization Methods
We study a class of overrelaxed bound optimization algorithms, and their relationship to standard bound optimizers, such as ExpectationMaximization, Iterative Scaling, CCCP and No...
Ruslan Salakhutdinov, Sam T. Roweis
ISF
2010
164views more  ISF 2010»
14 years 11 months ago
An SVM-based machine learning method for accurate internet traffic classification
Accurate and timely traffic classification is critical in network security monitoring and traffic engineering. Traditional methods based on port numbers and protocols have proven t...
Ruixi Yuan, Zhu Li, Xiaohong Guan, Li Xu
124
Voted
BMCBI
2007
113views more  BMCBI 2007»
15 years 2 months ago
Learning biophysically-motivated parameters for alpha helix prediction
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...
CIKM
2009
Springer
15 years 9 months ago
A machine learning approach for improved BM25 retrieval
Despite the widespread use of BM25, there have been few studies examining its effectiveness on a document description over single and multiple field combinations. We determine t...
Krysta Marie Svore, Christopher J. C. Burges
ACML
2009
Springer
15 years 6 months ago
Max-margin Multiple-Instance Learning via Semidefinite Programming
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
Yuhong Guo