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ACL
2006
13 years 10 months ago
Contextual Dependencies in Unsupervised Word Segmentation
Developing better methods for segmenting continuous text into words is important for improving the processing of Asian languages, and may shed light on how humans learn to segment...
Sharon Goldwater, Thomas L. Griffiths, Mark Johnso...
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 10 months 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
UAI
1997
13 years 10 months ago
Structure and Parameter Learning for Causal Independence and Causal Interaction Models
We begin by discussing causal independence models and generalize these models to causal interaction models. Causal interaction models are models that have independent mechanisms w...
Christopher Meek, David Heckerman
ICASSP
2011
IEEE
13 years 23 days ago
A segmentation method for textured images based on the maximum posterior mode criterion
We consider the problem of semi-supervised segmentation of textured images. Recently, reweighted belief propagation has been introduced as a solution for Bayesian inference with r...
Frédéric Lehmann
EDM
2008
127views Data Mining» more  EDM 2008»
13 years 10 months ago
Adaptive Test Design with a Naive Bayes Framework
Bayesian graphical models are commonly used to build student models from data. A number of standard algorithms are available to train Bayesian models from student skills assessment...
Michel C. Desmarais, Alejandro Villarreal, Michel ...