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» Mining with Noise Knowledge: Error Aware Data Mining
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KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 6 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
KDD
2012
ACM
207views Data Mining» more  KDD 2012»
11 years 8 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
KDD
2005
ACM
104views Data Mining» more  KDD 2005»
14 years 6 months ago
A hit-miss model for duplicate detection in the WHO drug safety database
The WHO Collaborating Centre for International Drug Monitoring in Uppsala, Sweden, maintains and analyses the world's largest database of reports on suspected adverse drug re...
Andrew Bate, G. Niklas Norén, Roland Orre
AINA
2010
IEEE
13 years 11 months ago
Towards Adaptive Mobile Mashups: Opportunities for Designing Effective Persuasive Technology on the Road
— Today’s vehicles and on-road infrastructures are equipped with a large number of sophisticated sensory devices. These sensory devices are capable of monitoring and providing ...
Flora Dilys Salim
KDD
2008
ACM
207views Data Mining» more  KDD 2008»
14 years 6 months ago
Active learning with direct query construction
Active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. Indeed, labeling data is a costly process, yet an ac...
Charles X. Ling, Jun Du