April 11, 2024, 4:42 a.m. | Taeuk Jeong, Yoon Mo Jung

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.06808v1 Announce Type: new
Abstract: Dimensionality reduction represents the process of generating a low dimensional representation of high dimensional data. Motivated by the formation control of mobile agents, we propose a nonlinear dynamical system for dimensionality reduction. The system consists of two parts; the control of neighbor points, addressing local structures, and the control of remote points, accounting for global structures. We also include a brief mathematical observation of the model and its numerical procedure. Numerical experiments are performed on …

abstract agents arxiv control cs.lg data dimensionality low mobile process representation type

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Machine Learning Engineer - Sr. Consultant level

@ Visa | Bellevue, WA, United States