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137
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KDD
2009
ACM
611views Data Mining» more  KDD 2009»
16 years 1 months ago
Fast 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-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 1 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
MOBISYS
2009
ACM
16 years 1 months ago
Leveraging smart phones to reduce mobility footprints
Mobility footprint refers to the size, weight, and energy demand of the hardware that must be carried by a mobile user to be effective at any time and place. The ideal of a zero m...
Stephen Smaldone, Benjamin Gilbert, Nilton Bila, L...
MOBIHOC
2009
ACM
16 years 1 months ago
Energy-efficient capture of stochastic events by global- and local-periodic network coverage
We consider a high density of sensors randomly placed in a geographical area for event monitoring. The monitoring regions of the sensors may have significant overlap, and a subset...
Shibo He, Jiming Chen, David K. Y. Yau, Huanyu Sha...
113
Voted
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
16 years 1 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
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