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» Learning of Boolean Functions Using Support Vector Machines
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ANNS
2007
13 years 9 months ago
Direct and indirect classification of high-frequency LNA performance using machine learning techniques
The task of determining low noise amplifier (LNA) high-frequency performance in functional testing is as challenging as designing the circuit itself due to the difficulties associa...
Peter C. Hung, Seán F. McLoone, Magdalena S...
ICTAI
2010
IEEE
13 years 5 months ago
Support Vector Methods for Sentence Level Machine Translation Evaluation
Recent work in the field of machine translation (MT) evaluation suggests that sentence level evaluation based on machine learning (ML) can outperform the standard metrics such as B...
Antoine Veillard, Elvina Melissa, Cassandra Theodo...
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
13 years 9 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
14 years 1 months ago
Incorporating prior knowledge with weighted margin support vector machines
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
Xiaoyun Wu, Rohini K. Srihari
BMCBI
2008
134views more  BMCBI 2008»
13 years 7 months ago
Prediction of protein-protein binding site by using core interface residue and support vector machine
Background: The prediction of protein-protein binding site can provide structural annotation to the protein interaction data from proteomics studies. This is very important for th...
Nan Li, Zhonghua Sun, Fan Jiang