Objective Function for Student Model Training via Knowledge Distillation

A team is training a compact 'student' model to emulate a powerful 'teacher' model. The training objective is to minimize a loss function that measures the divergence between the probability distributions of the student model's outputs and the teacher model's outputs for a given set of inputs. What is the primary goal of this optimization process?

Evaluating Model Parameters via Distribution Matching

Consider an optimization process where a model's parameters are adjusted to minimize a loss function that measures the difference between the model's output distribution and a target distribution over a dataset D'. True or False: Increasing the size and diversity of the dataset D' will always guarantee a better match to the target distribution, resulting in a lower final loss value.