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ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
15 years 2 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
AUTOMATICA
2011
14 years 1 months ago
Fast computation of minimal elementary decompositions of metabolic flux vectors
The concept of elementary flux vector is valuable in a number of applications of metabolic engineering. For instance, in metabolic flux analysis, each admissible flux vector ca...
Raphaël M. Jungers, Francisca Zamorano, Vince...
ATS
2009
IEEE
92views Hardware» more  ATS 2009»
14 years 7 months ago
M-IVC: Using Multiple Input Vectors to Minimize Aging-Induced Delay
Negative bias temperature instability (NBTI) has been a significant reliability concern in current digital circuit design due to its effect of increasing the path delay with time a...
Song Jin, Yinhe Han, Lei Zhang 0008, Huawei Li, Xi...
MLDM
2007
Springer
15 years 3 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
IFIP
2010
Springer
15 years 2 months ago
Vector Sensor Arrays in Underwater Acoustic Applications
Traditionally, ocean acoustic signals have been acquired using hydrophones, which measure the pressure field and are typically omnidirectional. A vector sensor measures both the ac...
Paulo Santos, Paulo Felisberto, Sérgio M. J...