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» Model Selection and Error Estimation
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NN
2008
Springer
143views Neural Networks» more  NN 2008»
15 years 2 months ago
A batch ensemble approach to active learning with model selection
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
135
Voted
TIP
2010
123views more  TIP 2010»
15 years 28 days ago
Optimizing Motion Compensated Prediction for Error Resilient Video Coding
—This paper is concerned with optimization of the motion compensated prediction framework to improve the error resilience of video coding for transmission over lossy networks. Fi...
Hua Yang, Kenneth Rose
130
Voted
ICPR
2008
IEEE
16 years 3 months ago
On using error bounds to optimize cost-sensitive multimodal biometric authentication
While using more biometric traits in multimodal biometric fusion can effectively increase the system robustness, often, the cost associated to adding additional systems is not con...
Norman Poh, Josef Kittler
MA
2010
Springer
94views Communications» more  MA 2010»
15 years 1 months ago
On sparse estimation for semiparametric linear transformation models
: Semiparametric linear transformation models have received much attention due to its high flexibility in modeling survival data. A useful estimating equation procedure was recent...
Hao Helen Zhang, Wenbin Lu, Hansheng Wang
148
Voted
BMCBI
2007
149views more  BMCBI 2007»
15 years 2 months ago
Robust imputation method for missing values in microarray data
Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
Dankyu Yoon, Eun-Kyung Lee, Taesung Park