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» Learning How to Propagate Using Random Probing
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BMCBI
2008
129views more  BMCBI 2008»
13 years 5 months ago
Prediction of the outcome of preoperative chemotherapy in breast cancer using DNA probes that provide information on both comple
Background: DNA microarray technology has emerged as a major tool for exploring cancer biology and solving clinical issues. Predicting a patient's response to chemotherapy is...
René Natowicz, Roberto Incitti, Euler Guima...
WWW
2007
ACM
14 years 5 months ago
Netprobe: a fast and scalable system for fraud detection in online auction networks
Given a large online network of online auction users and their histories of transactions, how can we spot anomalies and auction fraud? This paper describes the design and implemen...
Shashank Pandit, Duen Horng Chau, Samuel Wang, Chr...
CVPR
2000
IEEE
14 years 7 months ago
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
Song Chun Zhu, Xiuwen Liu
AAAI
2011
12 years 5 months ago
Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
Marion Neumann, Babak Ahmadi, Kristian Kersting
ICCV
2003
IEEE
14 years 7 months ago
Learning How to Inpaint from Global Image Statistics
Inpainting is the problem of filling-in holes in images. Considerable progress has been made by techniques that use the immediate boundary of the hole and some prior information o...
Anat Levin, Assaf Zomet, Yair Weiss