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PAMI
2011
14 years 11 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
PAMI
2012
13 years 6 months ago
Simultaneously Fitting and Segmenting Multiple-Structure Data with Outliers
Abstract—We propose a robust fitting framework, called Adaptive Kernel-Scale Weighted Hypotheses (AKSWH), to segment multiplestructure data even in the presence of a large number...
Hanzi Wang, Tat-Jun Chin, David Suter
BMCBI
2011
14 years 7 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
MM
2005
ACM
140views Multimedia» more  MM 2005»
15 years 9 months ago
Web image clustering by consistent utilization of visual features and surrounding texts
Image clustering, an important technology for image processing, has been actively researched for a long period of time. Especially in recent years, with the explosive growth of th...
Bin Gao, Tie-Yan Liu, Tao Qin, Xin Zheng, QianShen...
CLUSTER
2004
IEEE
15 years 8 months ago
Rolls: modifying a standard system installer to support user-customizable cluster frontend appliances
The Rocks toolkit [9], [7], [10] uses a graph-based framework to describe the configuration of all node types (termed appliances) that make up a complete cluster. With hundreds of...
Greg Bruno, Mason J. Katz, Federico D. Sacerdoti, ...