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ICDM
2007
IEEE
162views Data Mining» more  ICDM 2007»
15 years 2 months ago
Exploiting Network Structure for Active Inference in Collective Classification
Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
15 years 5 months ago
Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC)
Abstract. We address the problem of joint feature selection in multiple related classification or regression tasks. When doing feature selection with multiple tasks, usually one c...
Paramveer S. Dhillon, Brian Tomasik, Dean P. Foste...
IRI
2008
IEEE
15 years 5 months ago
Robust integration of multiple information sources by view completion
There are many applications where multiple data sources, each with its own features, are integrated in order to perform an inference task in an optimal way. Researchers have shown...
Shankara B. Subramanya, Baoxin Li, Huan Liu
BMCBI
2006
112views more  BMCBI 2006»
14 years 11 months ago
Distill: a suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins
Background: We describe Distill, a suite of servers for the prediction of protein structural features: secondary structure; relative solvent accessibility; contact density; backbo...
Davide Baù, Alberto J. M. Martin, Catherine...
ICML
2009
IEEE
15 years 11 months ago
Boosting with structural sparsity
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
John Duchi, Yoram Singer