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KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 2 days ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
KDD
2012
ACM
197views Data Mining» more  KDD 2012»
13 years 2 days ago
On the separability of structural classes of communities
Three major factors govern the intricacies of community extraction in networks: (1) the application domain includes a wide variety of networks of fundamentally different natures,...
Bruno D. Abrahao, Sucheta Soundarajan, John E. Hop...
KDD
2012
ACM
238views Data Mining» more  KDD 2012»
13 years 2 days ago
Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data
Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiativ...
Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A....
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CVPR
2012
IEEE
13 years 1 days ago
Discriminately decreasing discriminability with learned image filters
In machine learning and computer vision, input signals are often filtered to increase data discriminability. For example, preprocessing face images with Gabor band-pass filters ...
Jacob Whitehill, Javier R. Movellan
PODC
2012
ACM
13 years 1 days ago
Byzantine broadcast in point-to-point networks using local linear coding
The goal of Byzantine Broadcast (BB) is to allow a set of fault-free nodes to agree on information that a source node wants to broadcast to them, in the presence of Byzantine faul...
Guanfeng Liang, Nitin H. Vaidya
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