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» Semi-supervised Learning from General Unlabeled Data
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ICML
2004
IEEE
14 years 8 months ago
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
Zhihua Zhang, Dit-Yan Yeung, James T. Kwok
JCP
2006
118views more  JCP 2006»
13 years 7 months ago
Learning a Classification-based Glioma Growth Model Using MRI Data
Gliomas are malignant brain tumors that grow by invading adjacent tissue. We propose and evaluate a 3D classification-based growth model, CDM, that predicts how a glioma will grow ...
Marianne Morris, Russell Greiner, Jörg Sander...
ICML
2003
IEEE
14 years 8 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth
ICDM
2010
IEEE
135views Data Mining» more  ICDM 2010»
13 years 5 months ago
Learning a Bi-Stochastic Data Similarity Matrix
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
Fei Wang, Ping Li, Arnd Christian König
DAC
2011
ACM
12 years 7 months ago
AENEID: a generic lithography-friendly detailed router based on post-RET data learning and hotspot detection
In the era of deep sub-wavelength lithography for nanometer VLSI designs, manufacturability and yield issues are critical and need to be addressed during the key physical design i...
Duo Ding, Jhih-Rong Gao, Kun Yuan, David Z. Pan