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Found 2 papers, 2 papers with code
Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms
The integration of the new algorithms in Discrete Choice Models estimation software will significantly reduce the time required for model estimation and therefore enable researchers and practitioners to explore new approaches for the specification of choice models.
Stochastic Optimization
Optimization and Control
Enhancing Discrete Choice Models with Representation Learning
In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates.
