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» A general algorithm for data dependence analysis
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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 4 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...
IPSN
2004
Springer
15 years 9 months ago
Loss inference in wireless sensor networks based on data aggregation
In this paper, we consider the problem of inferring per node loss rates from passive end-to-end measurements in wireless sensor networks. Specifically, we consider the case of in...
Gregory Hartl, Baochun Li
PLDI
2012
ACM
13 years 6 months ago
Diderot: a parallel DSL for image analysis and visualization
Research scientists and medical professionals use imaging technology, such as computed tomography (CT) and magnetic resonance imaging (MRI) to measure a wide variety of biological...
Charisee Chiw, Gordon Kindlmann, John Reppy, Lamon...
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
16 years 1 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
PODC
2005
ACM
15 years 9 months ago
Facility location: distributed approximation
In this paper, we initiate the study of the approximability of the facility location problem in a distributed setting. In particular, we explore a trade-off between the amount of...
Thomas Moscibroda, Roger Wattenhofer