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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 7 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 12 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 9 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 3 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
16 years 3 days 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