—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...
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...
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...
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...
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, ...