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KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 5 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
TKDE
2008
114views more  TKDE 2008»
15 years 4 months ago
Neural-Based Learning Classifier Systems
UCS is a supervised learning classifier system that was introduced in 2003 for classification in data mining tasks. The representation of a rule in UCS as a univariate classificati...
Hai Huong Dam, Hussein A. Abbass, Chris Lokan, Xin...
JMLR
2010
202views more  JMLR 2010»
14 years 11 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
134
Voted
IJAHUC
2010
110views more  IJAHUC 2010»
15 years 3 months ago
Agenda driven mobility modelling
: Mobility modelling is an essential component of wireless and mobile networking research. Our proposed Agenda Driven Mobility Model takes into consideration a person’s social ac...
Qunwei Zheng, Xiaoyan Hong, Jun Liu, David Cordes,...
TPDS
2010
164views more  TPDS 2010»
14 years 11 months ago
Energy-Efficient Wake-Up Scheduling for Data Collection and Aggregation
The basic operation in such a network is the systematic gathering (with or without in-network aggregation) and transmitting of sensed data to a base station for further processing....
Yanwei Wu, Xiang-Yang Li, Yunhao Liu, Wei Lou