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» Iterated importance sampling in missing data problems
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BIBE
2001
IEEE
188views Bioinformatics» more  BIBE 2001»
15 years 2 months ago
Interrelated Two-way Clustering: An Unsupervised Approach for Gene Expression Data Analysis
DNA arrays can be used to measure the expression levels of thousands of genes simultaneously. Currently most research focuses on the interpretation of the meaning of the data. How...
Chun Tang, Li Zhang, Aidong Zhang, Murali Ramanath...
ECCV
2010
Springer
14 years 9 months ago
Element-Wise Factorization for N-View Projective Reconstruction
Sturm-Triggs iteration is a standard method for solving the projective factorization problem. Like other iterative algorithms, this method suffers from some common drawbacks such ...
Yuchao Dai, Hongdong Li, Mingyi He
DEXAW
2002
IEEE
127views Database» more  DEXAW 2002»
15 years 3 months ago
Enhanced Multi-Version Data Broadcast Schemes for Time-Constrained Mobile Computing Systems
In this paper, we study the data dissemination problem in time-constrained mobile computing systems (TCMCS) in which maximizing data currency (minimizing staleness) and meeting tr...
Hei-Wing Leung, Joe Chun-Hung Yuen, Kam-yiu Lam, E...
WCE
2007
15 years 18 hour ago
A Fast Multivariate Nearest Neighbour Imputation Algorithm
— Imputation of missing data is important in many areas, such as reducing non-response bias in surveys and maintaining medical documentation. Nearest neighbour (NN) imputation al...
Norman Solomon, Giles Oatley, Kenneth McGarry
BMCBI
2008
186views more  BMCBI 2008»
14 years 11 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells