Outputs (2)

A Note on Learning Dependence Under Severe Uncertainty (2014)
Conference Proceeding
Troffaes, M. C., Coolen, F. P., & Destercke, S. (2014). A Note on Learning Dependence Under Severe Uncertainty. In Information processing and management of uncertainty in knowledge-based systems : 15th International Conference, IPMU 2014, Montpellier, France, July 15-19, 2014 ; proceedings, part III (498-507). https://doi.org/10.1007/978-3-319-08852-5_51

We propose two models, one continuous and one categorical, to learn about dependence between two random variables, given only limited joint observations, but assuming that the marginals are precisely known. The continuous model focuses on the Gaussia... Read More about A Note on Learning Dependence Under Severe Uncertainty.

Multinomial logistic regression on Markov chains for crop rotation modelling (2014)
Conference Proceeding
Paton, L., Troffaes, M. C., Boatman, N., Hussein, M., & Hart, A. (2014). Multinomial logistic regression on Markov chains for crop rotation modelling. In Information processing and management of uncertainty in knowledge-based systems : 15th International Conference, IPMU 2014, Montpellier, France, July 15-19, 2014 ; proceedings, part III (476-485). https://doi.org/10.1007/978-3-319-08852-5_49

Often, in dynamical systems such as farmer’s crop choices, the dynamics are driven by external non-stationary factors, such as rainfall, temperature and agricultural input and output prices. Such dynamics can be modelled by a non-stationary Markov ch... Read More about Multinomial logistic regression on Markov chains for crop rotation modelling.