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ICDM
2007
IEEE
162views Data Mining» more  ICDM 2007»
13 years 8 months ago
Exploiting Network Structure for Active Inference in Collective Classification
Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 5 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
IIWAS
2008
13 years 6 months ago
Supporting mobile payment QOS by data mining GSM network traffic
In mobile commerce, short-message-service (SMS) is an important technique for delivering payment instruction. A payment model "SMS Credit" was proposed earlier [1]. Such...
Edison Lai, Simon Fong, Yang Hang
CICC
2011
106views more  CICC 2011»
12 years 4 months ago
A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons
Efforts to achieve the long-standing dream of realizing scalable learning algorithms for networks of spiking neurons in silicon have been hampered by (a) the limited scalability of...
Jae-sun Seo, Bernard Brezzo, Yong Liu, Benjamin D....
IMC
2010
ACM
13 years 2 months ago
Characterizing radio resource allocation for 3G networks
3G cellular data networks have recently witnessed explosive growth. In this work, we focus on UMTS, one of the most popular 3G mobile communication technologies. Our work is the f...
Feng Qian, Zhaoguang Wang, Alexandre Gerber, Zhuoq...