2024/05/20 by Elvis Han Cui, Cuicizion, Eliuvish
Computer Science · Engineering · #Advanced Numerical Analysis Techniques #Applications (stat.AP) #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Image Processing and 3D Reconstruction #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Robotic Mechanisms and Dynamics
paper · pdf · doi:10.48550/arxiv.2405.12390
openalex publication_date 2024/05/20 · openalex created_date 2024/05/23 · openalex updated_date 2026/07/28
Principal curve is a well-known statistical method oriented in manifold learning using concepts from differential geometry. In this paper, we propose a novel metric-based principal curve (MPC) method that learns one-dimensional manifold of spatial data. Synthetic datasets Real applications using MNIST dataset show that our method can learn the one-dimensional manifold well in terms of the shape.