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» Relevance Vector Machine Analysis of Functional Neuroimages
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DAGM
2010
Springer
14 years 10 months ago
Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma
Abstract. We consider an automated processing pipeline for tissue micro array analysis (TMA) of renal cell carcinoma. It consists of several consecutive tasks, which can be mapped ...
Peter J. Schüffler, Thomas J. Fuchs, Cheng So...
CIKM
2006
Springer
15 years 1 months ago
Incorporating query difference for learning retrieval functions in world wide web search
We discuss information retrieval methods that aim at serving a diverse stream of user queries such as those submitted to commercial search engines. We propose methods that emphasi...
Hongyuan Zha, Zhaohui Zheng, Haoying Fu, Gordon Su...
FLAIRS
2008
14 years 12 months ago
On Using SVM and Kolmogorov Complexity for Spam Filtering
As a side effect of e-marketing strategy the number of spam e-mails is rocketing, the time and cost needed to deal with spam as well. Spam filtering is one of the most difficult t...
Sihem Belabbes, Gilles Richard
MICRO
2005
IEEE
130views Hardware» more  MICRO 2005»
15 years 3 months ago
Exploiting Vector Parallelism in Software Pipelined Loops
An emerging trend in processor design is the addition of short vector instructions to general-purpose and embedded ISAs. Frequently, these extensions are employed using traditiona...
Samuel Larsen, Rodric M. Rabbah, Saman P. Amarasin...
ICPR
2000
IEEE
15 years 10 months ago
General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of D
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Jakob Vogdrup Hansen, Tom Heskes