[2M5-OS-24] OS-24

[2M5-OS-24-02] Meta-modeling of latent variable models

View point from the optimal transport distance

〇Tetsuo Furukawa¹, Hideaki Ishibashi¹ (1. Kyushu Institute of Technology)

Keywords:Meta-Learning, Optimal Transport Distance, Latent Variable Model, Generative Manifold Modeling

In this presentation, we discuss the learning theory behind the meta-modeling of latent variable models. Meta-modeling, as addressed in this presentation, represents a form of meta-learning. It involves the challenge of estimating a meta-model that describes a set of models derived from multiple learning tasks. A key challenge in the meta-modeling of latent variable models is ensuring consistency in the latent variables across different tasks. This presentation proposes a meta-learning method for latent variable models and explores its theoretical implications from the perspective of optimal transport distance.