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» Learning from Multiple Sources of Inaccurate Data
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114
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CORR
1998
Springer
125views Education» more  CORR 1998»
15 years 3 months ago
Automating Coreference: The Role of Annotated Training Data
Wereporthere ona studyof interannotatoragreementin the coreferencetask as defined by the MessageUnderstanding Conference(MUC-6and MUC-7).Basedon feedback from annotators, weclarif...
Lynette Hirschman, Patricia Robinson, John D. Burg...
BMCBI
2011
14 years 7 months ago
Cell Subset Prediction for Blood Genomic Studies
Background: Genome-wide transcriptional profiling of patient blood samples offers a powerful tool to investigate underlying disease mechanisms and personalized treatment decisions...
Christopher R. Bolen, Mohamed Uduman, Steven H. Kl...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 3 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
141
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CVPR
2010
IEEE
15 years 1 months ago
Multi-structure model selection via kernel optimisation
Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Tat-Jun Chin, David Suter, Hanzi Wang
ICML
2010
IEEE
15 years 4 months ago
Variable Selection in Model-Based Clustering: To Do or To Facilitate
Variable selection for cluster analysis is a difficult problem. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data ...
Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen,...