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» Semi-supervised Learning from General Unlabeled Data
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JMLR
2010
172views more  JMLR 2010»
13 years 2 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 8 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
WEBI
2010
Springer
13 years 5 months ago
DSP: Robust Semi-supervised Dimensionality Reduction Using Dual Subspace Projections
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
Su Yan, Sofien Bouaziz, Dongwon Lee
SAC
2004
ACM
14 years 1 months ago
An optimized approach for KNN text categorization using P-trees
The importance of text mining stems from the availability of huge volumes of text databases holding a wealth of valuable information that needs to be mined. Text categorization is...
Imad Rahal, William Perrizo
CIKM
2006
Springer
13 years 11 months ago
Knowing a web page by the company it keeps
Web page classification is important to many tasks in information retrieval and web mining. However, applying traditional textual classifiers on web data often produces unsatisfyi...
Xiaoguang Qi, Brian D. Davison