Uncovering the mystery of ensemble learning through the information theoretical lens
In this blog post, we introduce our paper on a theoretical framework of EL, which was presented at ICML 2022, the highest-level international conference in machine learning [1]. We proposed a fundamental theory that evaluates a given ensemble strategy by a well-grounded set of metrics. The theory answers the above question by revealing the strengths and weaknesses of an ensemble strategy in terms of its metrics. To demonstrate this, we analyzed a powerful ensemble strategy that uses diverse types of deep neural networks.
