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SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 7 days ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
93
Voted
BMCBI
2010
97views more  BMCBI 2010»
14 years 5 months ago
A semi-parametric Bayesian model for unsupervised differential co-expression analysis
Background: Differential co-expression analysis is an emerging strategy for characterizing disease related dysregulation of gene expression regulatory networks. Given pre-defined ...
Johannes M. Freudenberg, Siva Sivaganesan, Michael...
NAACL
2003
15 years 7 days ago
Unsupervised methods for developing taxonomies by combining syntactic and statistical information
This paper describes an unsupervised algorithm for placing unknown words into a taxonomy and evaluates its accuracy on a large and varied sample of words. The algorithm works by ï...
Dominic Widdows
99
Voted
DICTA
2003
15 years 8 days ago
False-Peaks-Avoiding Mean Shift Method for Unsupervised Peak-Valley Sliding Image Segmentation
The mean shift (MS) algorithm is sensitive to local peaks. In this paper, we show both empirically and analytically that when using sample data, the reconstructed PDF may have fals...
Hanzi Wang, David Suter
96
Voted
COLING
2008
15 years 10 days ago
Learning Entailment Rules for Unary Templates
Most work on unsupervised entailment rule acquisition focused on rules between templates with two variables, ignoring unary rules - entailment rules between templates with a singl...
Idan Szpektor, Ido Dagan