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ICML
2000
IEEE
15 years 10 months ago
Learning to Probabilistically Identify Authoritative Documents
We describe a model of document citation that learns to identify hubs and authorities in a set of linked documents, such as pages retrieved from the world wide web, or papers retr...
David Cohn, Huan Chang
ICML
2010
IEEE
14 years 10 months ago
Large Graph Construction for Scalable Semi-Supervised Learning
In this paper, we address the scalability issue plaguing graph-based semi-supervised learning via a small number of anchor points which adequately cover the entire point cloud. Cr...
Wei Liu, Junfeng He, Shih-Fu Chang
COLT
2004
Springer
15 years 3 months ago
Replacing Limit Learners with Equally Powerful One-Shot Query Learners
Different formal learning models address different aspects of human learning. Below we compare Gold-style learning—interpreting learning as a limiting process in which the lear...
Steffen Lange, Sandra Zilles
ICML
2003
IEEE
15 years 10 months ago
Adaptive Feature-Space Conformal Transformation for Imbalanced-Data Learning
When the training instances of the target class are heavily outnumbered by non-target training instances, SVMs can be ineffective in determining the class boundary. To remedy this...
Gang Wu, Edward Y. Chang
ICPR
2006
IEEE
15 years 10 months ago
On Kernel Selection in Relevance Vector Machines Using Stability Principle
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
Dmitry Kropotov, Nikita Ptashko, Oleg Vasiliev, Dm...