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» Compiling Bayesian Networks Using Variable Elimination
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UAI
2008
13 years 9 months ago
Learning Arithmetic Circuits
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
Daniel Lowd, Pedro Domingos
CMPB
2010
171views more  CMPB 2010»
13 years 2 months ago
Metabolica: A statistical research tool for analyzing metabolic networks
Steady state flux balance analysis (FBA) for cellular metabolism is used, e.g., to seek information on the activity of the different pathways under equilibrium conditions, or as a...
Jenni Heino, Daniela Calvetti, Erkki Somersalo
IDEAL
2003
Springer
14 years 22 days ago
A Two-Stage Bayesian Network for Effective Development of Conversational Agent
Conversational agent is a system that provides user with proper information and maintains the context of dialogue based on natural language. When experts design the network for con...
Jin-Hyuk Hong, Sung-Bae Cho
AAAI
1996
13 years 8 months ago
Goal Oriented Symbolic Propagation in Bayesian Networks
The paper presents an efficient goal oriented algorithm for symbolic propagation in Bayesian networks. The proposed algorithm performs symbolic propagation using numerical methods...
Enrique Castillo, José Manuel Gutiér...
SASO
2009
IEEE
14 years 2 months ago
Optimising Sensor Layouts for Direct Measurement of Discrete Variables
An optimal sensor layout is attained when a limited number of sensors are placed in an area such that the cost of the placement is minimised while the value of the obtained inform...
X. Rosalind Wang, George Mathews, Don Price, Mikha...