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NIPS
2004
13 years 9 months ago
Detecting Significant Multidimensional Spatial Clusters
Assume a uniform, multidimensional grid of bivariate data, where each cell of the grid has a count ci and a baseline bi. Our goal is to find spatial regions (d-dimensional rectang...
Daniel B. Neill, Andrew W. Moore, Francisco Pereir...
CMSB
2006
Springer
13 years 11 months ago
Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis
Abstract. The important research objective of identifying genes with similar behavior with respect to different conditions has recently been tackled with biclustering techniques. I...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
SOCO
2008
Springer
13 years 7 months ago
A particular Gaussian mixture model for clustering and its application to image retrieval
We introduce a new method for data clustering based on a particular Gaussian mixture model (GMM). Each cluster of data, modeled as a GMM into an input space, is interpreted as a hy...
Hichem Sahbi
ICDCS
2012
IEEE
11 years 10 months ago
FindingHuMo: Real-Time Tracking of Motion Trajectories from Anonymous Binary Sensing in Smart Environments
Abstract—In this paper we have proposed and designed FindingHuMo (Finding Human Motion), a real-time user tracking system for Smart Environments. FindingHuMo can perform device-f...
Debraj De, Wen-Zhan Song, Mingsen Xu, Cheng-Liang ...
PODS
2005
ACM
115views Database» more  PODS 2005»
14 years 8 months ago
A divide-and-merge methodology for clustering
We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...