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» Unsupervised Analysis for Decipherment Problems
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NIPS
2007
15 years 4 days ago
Supervised Topic Models
We introduce supervised latent Dirichlet allocation (sLDA), a statistical model of labelled documents. The model accommodates a variety of response types. We derive a maximum-like...
David M. Blei, Jon D. McAuliffe
TCS
2008
14 years 10 months ago
Detection of subtle variations as consensus motifs
We address the problem of detecting consensus motifs, that occur with subtle variations, across multiple sequences. These are usually functional domains in DNA sequences such as t...
Matteo Comin, Laxmi Parida
IJCAI
2007
15 years 4 days ago
Document Summarization Using Conditional Random Fields
Many methods, including supervised and unsupervised algorithms, have been developed for extractive document summarization. Most supervised methods consider the summarization task ...
Dou Shen, Jian-Tao Sun, Hua Li, Qiang Yang, Zheng ...
CVPR
2006
IEEE
16 years 22 days ago
Clustering Appearance for Scene Analysis
We propose a new approach called "appearance clustering" for scene analysis. The key idea in this approach is that the scene points can be clustered according to their s...
Sanjeev J. Koppal, Srinivasa G. Narasimhan
KDD
2006
ACM
115views Data Mining» more  KDD 2006»
15 years 11 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...