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» Approximate data mining in very large relational data
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CISS
2007
IEEE
15 years 8 months ago
Collector Receiver Design for Data Collection and Localization in Sensor-driven Networks
— We consider a sensor network in which the sensors communicate at will when they have something to report, without prior coordination with other sensors or with data collection ...
Bharath Ananthasubramaniam, Upamanyu Madhow
KDD
2012
ACM
194views Data Mining» more  KDD 2012»
13 years 4 months ago
A sparsity-inducing formulation for evolutionary co-clustering
Traditional co-clustering methods identify block structures from static data matrices. However, the data matrices in many applications are dynamic; that is, they evolve smoothly o...
Shuiwang Ji, Wenlu Zhang, Jun Liu
VLDB
2002
ACM
108views Database» more  VLDB 2002»
15 years 1 months ago
Energy-performance trade-offs for spatial access methods on memory-resident data
Abstract. The proliferation of mobile and pervasive computing devices has brought energy constraints into the limelight. Energy-conscious design is important at all levels of syste...
Ning An, Sudhanva Gurumurthi, Anand Sivasubramania...
MM
2009
ACM
221views Multimedia» more  MM 2009»
15 years 8 months ago
Using large-scale web data to facilitate textual query based retrieval of consumer photos
The rapid popularization of digital cameras and mobile phone cameras has lead to an explosive growth of consumer photo collections. In this paper, we present a (quasi) real-time t...
Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
15 years 8 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon