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» Estimating Likelihoods for Topic Models
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PKDD
2005
Springer
96views Data Mining» more  PKDD 2005»
15 years 5 months ago
Testing Theories in Particle Physics Using Maximum Likelihood and Adaptive Bin Allocation
We describe a methodology to assist scientists in quantifying the degree of evidence in favor of a new proposed theory compared to a standard baseline theory. The figure of merit ...
Bruce Knuteson, Ricardo Vilalta
BMCBI
2007
158views more  BMCBI 2007»
14 years 12 months ago
Penalized likelihood for sparse contingency tables with an application to full-length cDNA libraries
Background: The joint analysis of several categorical variables is a common task in many areas of biology, and is becoming central to systems biology investigations whose goal is ...
Corinne Dahinden, Giovanni Parmigiani, Mark C. Eme...
EMNLP
2008
15 years 1 months ago
Bayesian Unsupervised Topic Segmentation
This paper describes a novel Bayesian approach to unsupervised topic segmentation. Unsupervised systems for this task are driven by lexical cohesion: the tendency of wellformed se...
Jacob Eisenstein, Regina Barzilay
ECCV
2008
Springer
16 years 1 months ago
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Cassio Polpo de Campos, Yan Tong, Qiang Ji
ICASSP
2008
IEEE
15 years 6 months ago
Maximum likelihood approach to speech enhancement for noisy reverberant signals
This paper proposes a speech enhancement method for signals contaminated by room reverberation and additive background noise. The following conditions are assumed: (1) The spectra...
Takuya Yoshioka, Tomohiro Nakatani, Takafumi Hikic...