Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Approximation algorithms
Learning Bayesian Networks
Learn to Tango with D
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Bayesian Networks: An Introduction
Bayesian Networks: An Introduction
A new stochastic algorithm for strategy optimisation in Bayesian influence diagrams
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Stochastic techniques in influence diagrams for learning bayesian network structure
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
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The goal of the ramified optimal transport is to find an optimal transport path between two given probability measures. One measure can be identified with a source while the other one with a target. The problem is well known to be NP---hard. We develop an algorithm for solving a ramified optimal transport problem within the framework of Bayesian networks. It is based on the decision strategy optimisation technique that utilises self---annealing ideas of Chen---style stochastic optimisation. Resulting transport paths are represented in the form of tree---shaped structures. The effectiveness of the algorithm has been tested on computer---generated examples.