Abstract: Knowledge Distillation (KD) is an effective model compression approach to transfer knowledge from a larger network to a smaller one. Existing state-of-the-art methods mostly focus on feature ...
Abstract: This study applies the random parameter logit model (RPL), random parameter logit model with mean and variance heterogeneity (RPLMV), random forest (RF), and extreme random tree (ERT) to ...
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