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KDD
2009
ACM
227views Data Mining» more  KDD 2009»
14 years 9 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
IPSN
2010
Springer
14 years 1 months ago
Ear-phone: an end-to-end participatory urban noise mapping system
A noise map facilitates monitoring of environmental noise pollution in urban areas. It can raise citizen awareness of noise pollution levels, and aid in the development of mitigat...
Rajib Kumar Rana, Chun Tung Chou, Salil S. Kanhere...
BMCBI
2008
95views more  BMCBI 2008»
13 years 8 months ago
Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method
Background: Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC) analysis has been used for this purpose, but ...
Joseph W. Foley, Fumiaki Katagiri
ALT
1999
Springer
14 years 23 days ago
PAC Learning with Nasty Noise
We introduce a new model for learning in the presence of noise, which we call the Nasty Noise model. This model generalizes previously considered models of learning with noise. Th...
Nader H. Bshouty, Nadav Eiron, Eyal Kushilevitz
FCCM
2003
IEEE
148views VLSI» more  FCCM 2003»
14 years 1 months ago
A Hardware Gaussian Noise Generator for Channel Code Evaluation
Hardware simulation of channel codes offers the potential of improving code evaluation speed by orders of magnitude over workstation- or PC-based simulation. We describe a hardwar...
Dong-U Lee, Wayne Luk, John D. Villasenor, Peter Y...