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BIOINFORMATICS
2006
118views more  BIOINFORMATICS 2006»
15 years 7 months ago
A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription
Motivation Quantitative estimation of the regulatory relationship between transcription factors and genes is a fundamental stepping stone when trying to develop models of cellular...
Guido Sanguinetti, Magnus Rattray, Neil D. Lawrenc...
AIEDU
2005
185views more  AIEDU 2005»
15 years 7 months ago
A Bayesian Student Model without Hidden Nodes and its Comparison with Item Response Theory
The Bayesian framework offers a number of techniques for inferring an individual's knowledge state from evidence of mastery of concepts or skills. A typical application where ...
Michel C. Desmarais, Xiaoming Pu
JMLR
2010
157views more  JMLR 2010»
15 years 6 months ago
Kronecker Graphs: An Approach to Modeling Networks
How can we generate realistic networks? In addition, how can we do so with a mathematically tractable model that allows for rigorous analysis of network properties? Real networks ...
Jure Leskovec, Deepayan Chakrabarti, Jon M. Kleinb...
TASLP
2011
15 years 2 months ago
A Generative Student Model for Scoring Word Reading Skills
—This paper presents a novel student model intended to automate word-list-based reading assessments in a classroom setting, specifically for a student population that includes b...
Joseph Tepperman, Sungbok Lee, Shrikanth Narayanan...
CVPR
2008
IEEE
16 years 9 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...