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» An Instance Selection Approach to Multiple Instance Learning
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IJCV
2006
206views more  IJCV 2006»
14 years 9 months ago
Random Sampling for Subspace Face Recognition
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...
Xiaogang Wang, Xiaoou Tang
BMCBI
2005
148views more  BMCBI 2005»
14 years 9 months ago
Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments
Background: Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is ...
Xin Gao, Peter X. K. Song
AMAI
2004
Springer
15 years 3 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
SDM
2004
SIAM
141views Data Mining» more  SDM 2004»
14 years 11 months ago
Active Mining of Data Streams
Most previously proposed mining methods on data streams make an unrealistic assumption that "labelled" data stream is readily available and can be mined at anytime. Howe...
Wei Fan, Yi-an Huang, Haixun Wang, Philip S. Yu
CEC
2010
IEEE
14 years 10 months ago
Iterated local search vs. hyper-heuristics: Towards general-purpose search algorithms
An important challenge within hyper-heuristic research is to design search methodologies that work well, not only across different instances of the same problem, but also across di...
Edmund K. Burke, Timothy Curtois, Matthew R. Hyde,...