The analysis from nonlinear distance metric to kernel-based prescription prediction system

DOI10.23952/jnva.5.2021.2.01OpenAlexW4241539411MaRDI QIDQ3383188

Chi-Feng Hung, Ophir Frieder, Hao-Ren Yao, Der-Chen E. Chang

Publication date: 23 September 2021

Published in: Journal of Nonlinear and Variational Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2102.02446

zbMATH Keywords

geometrymachine learninggraph kerneldeep metric learning

Mathematics Subject Classification ID

Operator theory (47-XX) Functional analysis (46-XX)

Related Items (2)

Reilly-type inequality for the \(\Phi\)-Laplace operator on semislant submanifolds of Sasakian space forms ⋮ Heat kernels on unit spheres and applications to graph kernels

Uses Software

• Adam
• t-SNE

Cites Work

• Heat kernels for a family of Grushin operators
• Hopf fibration: Geodesics and distances
• Heat kernels for elliptic and sub-elliptic operators. Methods and techniques
• Metric Learning: A Survey
• Nonlinear Deep Kernel Learning for Image Annotation
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