4 papers
Laws of Learning Dynamics and the Core of Learners
Inkee Jung, Siu Cheong Lau
We formulate the fundamental laws governing learning dynamics, namely the conservation law and the decrease of total entropy. Within this framework, we introduce an entropy-based l…
Stable Vectorization of Persistent Laplacians via Spectral Descriptors
Inkee Jung, Wonwoo Kang, Heehyun Park
Persistence images vectorize persistence diagrams into stable, finite-dimensional features. Inspired by this idea, we developed a vectorization framework for the spectral informati…
A logifold structure on measure space
Inkee Jung, Siu-Cheong Lau
In this paper,we develop a local-to-global and measure-theoretical approach to understand datasets. The idea is to take network models with restricted domains as local charts of da…
Logifold: A Geometrical Foundation of Ensemble Machine Learning
Inkee Jung, Siu-Cheong Lau
We present a local-to-global and measure-theoretical approach to understanding datasets. The core idea is to formulate a logifold structure and to interpret network models with res…