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» Clustering performance data efficiently at massive scales
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MOBIHOC
2005
ACM
16 years 5 days ago
Power balanced coverage-time optimization for clustered wireless sensor networks
We consider a wireless sensor network in which sensors are grouped into clusters, each with its own cluster head (CH). Each CH collects data from sensors in its cluster and relays...
Tao Shu, Marwan Krunz, Sarma B. K. Vrudhula
156
Voted
EMNETS
2007
15 years 4 months ago
Image browsing, processing, and clustering for participatory sensing: lessons from a DietSense prototype
Imagers are an increasingly significant source of sensory observations about human activity and the urban environment. ImageScape is a software tool for processing, clustering, an...
Sasank Reddy, Andrew Parker, Josh Hyman, Jeff Burk...
95
Voted
TSMC
1998
96views more  TSMC 1998»
15 years 7 days ago
The MDS-ANAVA technique for assessing knowledge representation differences between skill groups
—Knowledge representation is one of important factors that determine human performance on cognitive tasks. Due to different levels of experience, different groups of people may d...
Nong Ye
116
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Online Kernel SVM for real-time fMRI brain state prediction
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...
102
Voted
PVLDB
2008
116views more  PVLDB 2008»
15 years 2 days ago
Tighter estimation using bottom k sketches
Summaries of massive data sets support approximate query processing over the original data. A basic aggregate over a set of records is the weight of subpopulations specified as a ...
Edith Cohen, Haim Kaplan