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» Sampling Techniques for Kernel Methods
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RECOMB
2004
Springer
15 years 3 months ago
Application of Kernel Method to Reveal Subtypes of TF Binding Motifs
Transcription factor binding sites often contain several subtypes of sequences that follow not just one but several different patterns. We developed a novel sensitive method based ...
Alexander E. Kel, Yuri Tikunov, Nico Voss, Jü...
FCSC
2007
159views more  FCSC 2007»
14 years 9 months ago
Ranking with uncertain labels and its applications
1 The techniques for image analysis and classi cation generally consider the image sample labels xed and without uncertainties. The rank regression problem is studied in this pape...
Shuicheng Yan, Huan Wang, Jianzhuang Liu, Xiaoou T...
BMCBI
2010
150views more  BMCBI 2010»
14 years 7 months ago
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
ICPR
2006
IEEE
15 years 10 months ago
Weakly Supervised Learning on Pre-image Problem in Kernel Methods
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
Weishi Zheng, Jian-Huang Lai, Pong Chi Yuen
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ICASSP
2009
IEEE
15 years 4 months ago
Sampling signals with finite rate of innovation in the presence of noise
Recently, it has been shown that it is possible to sample non-bandlimited signals that possess a limited number of degrees of freedom and uniquely reconstruct them from a finite ...
Pier Luigi Dragotti, Felix Homann