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» Learning from Multiple Sources of Inaccurate Data
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CVIU
2004
132views more  CVIU 2004»
13 years 7 months ago
Layered representations for learning and inferring office activity from multiple sensory channels
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
Nuria Oliver, Ashutosh Garg, Eric Horvitz
CVPR
2010
IEEE
13 years 7 months ago
Boosting for transfer learning with multiple sources
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...
Yi Yao, Gianfranco Doretto
KDD
2008
ACM
206views Data Mining» more  KDD 2008»
14 years 7 months ago
Identifying biologically relevant genes via multiple heterogeneous data sources
Selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. Recent development in bioin...
Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Y...
DILS
2005
Springer
14 years 1 months ago
Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources
Abstract. We present INDUS (Intelligent Data Understanding System), a federated, query-centric system for knowledge acquisition from autonomous, distributed, semantically heterogen...
Doina Caragea, Jyotishman Pathak, Jie Bao, Adrian ...
PKDD
2010
Springer
138views Data Mining» more  PKDD 2010»
13 years 5 months ago
Constructing Nonlinear Discriminants from Multiple Data Views
There are many situations in which we have more than one view of a single data source, or in which we have multiple sources of data that are aligned. We would like to be able to bu...
Tom Diethe, David R. Hardoon, John Shawe-Taylor