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CIKM
2009
Springer
13 years 10 months ago
Heterogeneous cross domain ranking in latent space
Traditional ranking mainly focuses on one type of data source, and effective modeling still relies on a sufficiently large number of labeled or supervised examples. However, in m...
Bo Wang, Jie Tang, Wei Fan, Songcan Chen, Zi Yang,...
KDD
2009
ACM
163views Data Mining» more  KDD 2009»
14 years 6 months ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer
CVPR
2012
IEEE
11 years 8 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
JMLR
2006
169views more  JMLR 2006»
13 years 5 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
GECCO
2005
Springer
189views Optimization» more  GECCO 2005»
13 years 11 months ago
Molecular programming: evolving genetic programs in a test tube
We present a molecular computing algorithm for evolving DNA-encoded genetic programs in a test tube. The use of synthetic DNA molecules combined with biochemical techniques for va...
Byoung-Tak Zhang, Ha-Young Jang