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AAAI
2004
11 years 2 months ago
Error Detection and Impact-Sensitive Instance Ranking in Noisy Datasets
Given a noisy dataset, how to locate erroneous instances and attributes and rank suspicious instances based on their impacts on the system performance is an interesting and import...
Xingquan Zhu, Xindong Wu, Ying Yang
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
9 years 3 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
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