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» Incremental and Decremental Support Vector Machine Learning
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BMCBI
2010
98views more  BMCBI 2010»
14 years 10 months ago
Learning to predict expression efficacy of vectors in recombinant protein production
Background: Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is t...
Wen-Ching Chan, Po-Huang Liang, Yan-Ping Shih, Uen...
NPL
2008
130views more  NPL 2008»
14 years 9 months ago
Adaptive Inverse Control of Excitation System with Actuator Uncertainty
: - This paper addresses an inverse controller design for excitation system with changing parameters and nonsmooth nonlinearities in the actuator. The existence of such nonlinearit...
Xiaofang Yuan, Yaonan Wang, Liang-Hong Wu
AIME
2009
Springer
14 years 7 months ago
Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach
Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scan...
Aliaksei Kerhet, Cormac Small, Harvey Quon, Terenc...
BMCBI
2011
14 years 4 months ago
DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning
Background: Accurate identification of protein domain boundaries is useful for protein structure determination and prediction. However, predicting protein domain boundaries from a...
Jesse Eickholt, Xin Deng, Jianlin Cheng
NIPS
2001
14 years 11 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson