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» Bayesian Learning of Sparse Classifiers
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JMLR
2008
116views more  JMLR 2008»
13 years 7 months ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li
SDM
2010
SIAM
144views Data Mining» more  SDM 2010»
13 years 9 months ago
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
WWW
2008
ACM
14 years 8 months ago
Learning transportation mode from raw gps data for geographic applications on the web
Geographic information has spawned many novel Web applications where global positioning system (GPS) plays important roles in bridging the applications and end users. Learning kno...
Yu Zheng, Like Liu, Longhao Wang, Xing Xie
JIB
2006
220views more  JIB 2006»
13 years 7 months ago
An assessment of machine and statistical learning approaches to inferring networks of protein-protein interactions
Protein-protein interactions (PPI) play a key role in many biological systems. Over the past few years, an explosion in availability of functional biological data obtained from hi...
Fiona Browne, Haiying Wang, Huiru Zheng, Francisco...
ICDM
2007
IEEE
289views Data Mining» more  ICDM 2007»
14 years 2 months ago
Latent Dirichlet Conditional Naive-Bayes Models
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
Arindam Banerjee, Hanhuai Shan