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CIKM
2009
Springer
15 years 10 months ago
Efficient feature weighting methods for ranking
Feature weighting or selection is a crucial process to identify an important subset of features from a data set. Removing irrelevant or redundant features can improve the generali...
Hwanjo Yu, Jinoh Oh, Wook-Shin Han
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 8 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
192
Voted
BMCBI
2010
136views more  BMCBI 2010»
15 years 7 months ago
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, producti...
Yevhen Vainshtein, Mayka Sanchez, Alvis Brazma, Ma...
MMS
2006
15 years 6 months ago
Collaborative image retrieval via regularized metric learning
In content-based image retrieval (CBIR), relevant images are identified based on their similarities to query images. Most CBIR algorithms are hindered by the semantic gap between ...
Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu
DCC
2005
IEEE
16 years 6 months ago
The Markov Expert for Finding Episodes in Time Series
We describe a domain-independent, unsupervised algorithm for refined segmentation of time series data into meaningful episodes, focusing on the problem of text segmentation. The V...
Jimming Cheng, Michael Mitzenmacher