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ML
2010
ACM
151views Machine Learning» more  ML 2010»
15 years 2 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
AUTOMATICA
2008
123views more  AUTOMATICA 2008»
15 years 4 months ago
Identification with stochastic sampling time jitter
This work investigates how stochastic sampling jitter noise affects the result of system identification, and proposes a modification of known approaches to mitigate the effects of...
Frida Eng, Fredrik Gustafsson
CEC
2009
IEEE
15 years 11 months ago
Performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on the CEC09 test problems
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...
BMCBI
2010
97views more  BMCBI 2010»
15 years 4 months ago
Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear a
Background: Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as canc...
Maris Lapinsh, Jarl E. S. Wikberg
ACCV
2010
Springer
15 years 6 months ago
Ghost-free High Dynamic Range Imaging
Most high dynamic range image (HDRI) algorithms assume stationary scene for registering multiple images which are taken under different exposure settings. In practice, however, the...
Yong Seok Heo (Seoul National University), Kyoung ...