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CHI
2009
ACM
16 years 5 months ago
Two studies of opportunistic programming: interleaving web foraging, learning, and writing code
This paper investigates the role of online resources in problem solving. We look specifically at how programmers--an exemplar form of knowledge workers--opportunistically interlea...
Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira ...
CIVR
2008
Springer
271views Image Analysis» more  CIVR 2008»
15 years 6 months ago
Multiple feature fusion by subspace learning
Since the emergence of extensive multimedia data, feature fusion has been more and more important for image and video retrieval, indexing and annotation. Existing feature fusion t...
Yun Fu, Liangliang Cao, Guodong Guo, Thomas S. Hua...
SDM
2010
SIAM
256views Data Mining» more  SDM 2010»
15 years 6 months ago
The Application of Statistical Relational Learning to a Database of Criminal and Terrorist Activity
We apply statistical relational learning to a database of criminal and terrorist activity to predict attributes and event outcomes. The database stems from a collection of news ar...
B. Delaney, Andrew S. Fast, W. M. Campbell, C. J. ...
BMCBI
2010
143views more  BMCBI 2010»
15 years 4 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
IJCV
2008
192views more  IJCV 2008»
15 years 4 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...