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» A Bayesian Approach to Semi-Supervised Learning
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BMCBI
2010
147views more  BMCBI 2010»
13 years 8 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
FLAIRS
2007
13 years 11 months ago
Memory-Prediction Framework for Pattern Recognition: Performance and Suitability of the Bayesian Model of Visual Cortex
This paper explores an inferential system for recognizing visual patterns. The system is inspired by a recent memoryprediction theory and models the high-level architecture of the...
Saulius Juozas Garalevicius
CORR
2008
Springer
98views Education» more  CORR 2008»
13 years 8 months ago
Bayesian Optimisation Algorithm for Nurse Scheduling
: Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimizatio...
Jingpeng Li, Uwe Aickelin
IJCNN
2006
IEEE
14 years 2 months ago
Sparse Bayesian Models: Bankruptcy-Predictors of Choice?
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
Bernardete Ribeiro, Armando Vieira, João Ca...
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