Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models

Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models

Specifying utility functions is a key step towards applying the discrete choice framework for understanding the behaviour processes that govern user choices. However, identifying the utility function specifications that best model and explain the observed choices can be a very challenging and time-c...

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Bibliographic Details
Main Authors: Bierlaire, M. (Author), Ortelli, N. (Author), Pereira, F.C (Author), Rodrigues, F. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
automatic relevance determination
Automatic relevance determination
automatic utility specification
Automatic utility specification
Bayesian
Bayesian networks
Discrete choice
Discrete choice models
Doubly stochastic
doubly stochastic variational inference
Doubly stochastic variational inference
Function specification
Inference engines
Large dataset
Specifications
Stochastic models
Stochastic systems
Utility functions
Variational inference
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