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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 5 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
ACL
2004
13 years 8 months ago
Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models
We describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. The first model, which we call the Sense model, builds on the work of Diab ...
Indrajit Bhattacharya, Lise Getoor, Yoshua Bengio
NIPS
2003
13 years 8 months ago
A Model for Learning the Semantics of Pictures
We propose an approach to learning the semantics of images which allows us to automatically annotate an image with keywords and to retrieve images based on text queries. We do thi...
Victor Lavrenko, R. Manmatha, Jiwoon Jeon
ICDE
2006
IEEE
194views Database» more  ICDE 2006»
14 years 8 months ago
The Gauss-Tree: Efficient Object Identification in Databases of Probabilistic Feature Vectors
In applications of biometric databases the typical task is to identify individuals according to features which are not exactly known. Reasons for this inexactness are varying meas...
Alexey Pryakhin, Christian Böhm, Matthias Sch...
IPM
2007
182views more  IPM 2007»
13 years 7 months ago
A probabilistic music recommender considering user opinions and audio features
A recommender system has an obvious appeal in an environment where the amount of on-line information vastly outstrips any individual’s capability to survey. Music recommendation...
Qing Li, Sung-Hyon Myaeng, Byeong Man Kim