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» On Kernel Methods for Relational Learning
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ICML
2009
IEEE
16 years 4 months ago
Learning spectral graph transformations for link prediction
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Andreas Lommatzsch, Jérôme Kunegis
159
Voted
CVPR
2012
IEEE
13 years 5 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
NIPS
2004
15 years 4 months ago
An Application of Boosting to Graph Classification
This paper presents an application of Boosting for classifying labeled graphs, general structures for modeling a number of real-world data, such as chemical compounds, natural lan...
Taku Kudo, Eisaku Maeda, Yuji Matsumoto
CVPR
2012
IEEE
13 years 5 months ago
Supervised hashing with kernels
Recent years have witnessed the growing popularity of hashing in large-scale vision problems. It has been shown that the hashing quality could be boosted by leveraging supervised ...
Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, Shi...
ECTEL
2007
Springer
15 years 9 months ago
Profiled Search Methods for e-Learning Systems
Most currently used e-Learning Systems do not often offer search functionality. Even if methods are provided to search for Learning Objects (LOs), they don’t usually utilize info...
Tomasz Orzechowski, Sebastian Ernst, Andrzej Dziec...