Learning Influence among Interacting Markov Chains

Zhang, Dong, Gatica-perez, Daniel, Bengio, Samy, Roy, Deb

Dec-31-2006–Neural Information Processing Systems

We present a model that learns the influence of interacting Markov chains within a team. The proposed model is a dynamic Bayesian network (DBN) with a two-level structure: individual-level and group-level.

influence model, participant, two-level influence model, (16 more...)

Neural Information Processing Systems

Dec-31-2006

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Country:
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Industry:
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Technology:
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models
  - Undirected Networks > Markov Models (1.00)
  - Directed Networks > Bayesian Learning (0.89)

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