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AAAI
2010
13 years 9 months ago
G-Optimal Design with Laplacian Regularization
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
AAAI
2010
13 years 9 months ago
Informed Lifting for Message-Passing
Lifted inference, handling whole sets of indistinguishable objects together, is critical to the effective application of probabilistic relational models to realistic real world ta...
Kristian Kersting, Youssef El Massaoudi, Fabian Ha...
AAAI
2010
13 years 9 months ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos
APVIS
2007
13 years 9 months ago
A comparison of vertex ordering algorithms for large graph visualization
In this study, we examine the use of graph ordering algorithms for visual analysis of data sets using visual similarity matrices. Visual similarity matrices display the relationsh...
Christopher Mueller, Benjamin Martin, Andrew Lumsd...
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
13 years 9 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang