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ICDM
2009
IEEE
92views Data Mining» more  ICDM 2009»
14 years 9 months ago
Semi-supervised Multi-task Learning with Task Regularizations
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
Fei Wang, Xin Wang, Tao Li
CVPR
2009
IEEE
16 years 6 months ago
Shared Kernel Information Embedding for Discriminative Inference
Latent Variable Models (LVM), like the Shared-GPLVM and the Spectral Latent Variable Model, help mitigate over- fitting when learning discriminative methods from small or modera...
David J. Fleet, Leonid Sigal, Roland Memisevic
CEC
2009
IEEE
15 years 6 months ago
Coevolution of simulator proxies and sampling strategies for petroleum reservoir modeling
— Reservoir modeling is an on-going activity during the production life of a reservoir. One challenge to constructing accurate reservoir models is the time required to carry out ...
Tina Yu, Dave Wilkinson
EUROPAR
2004
Springer
15 years 3 months ago
Efficient Parallel Hierarchical Clustering
Hierarchical agglomerative clustering (HAC) is a common clustering method that outputs a dendrogram showing all N levels of agglomerations where N is the number of objects in the d...
Manoranjan Dash, Simona Petrutiu, Peter Scheuerman...
MCS
2010
Springer
15 years 1 months ago
Choosing Parameters for Random Subspace Ensembles for fMRI Classification
Abstract. Functional magnetic resonance imaging (fMRI) is a noninvasive and powerful method for analysis of the operational mechanisms of the brain. fMRI classification poses a sev...
Ludmila I. Kuncheva, Catrin O. Plumpton