Work

Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science

Year: 2017

Type: article

Abstract: nearest neighbors and only connect to those without sacrificing quality of results. This approach can simplify and accelerate computation; we illustrate this with experimental results in spectral clustering of large-scale datasets.

Source: PubMed

DOI: 10.48550/arxiv.1711.04712

Authors: Linderman, George C., Mishne, Gal, Kluger, Yuval, Steinerberger, Stefan

Institution: Yale University

Language: English

Topic: Advanced Clustering Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, United States-Israel Binational Science Foundation, National Institutes of Health, National Cancer Institute, National Institute of General Medical Sciences, National Institute of Neurological Disorders and Stroke

Awards: CRCNS: Sensory-Motor Integration in Mammalian Brian: experiment, analysis, modeling, Efficient Methods for Imputation, Dimensionality Reduction, and Visualization of Single Cell RNA-Sequencing Data, G5561132364, Medical Scientist Training Program, G9000234276, Yale Clinical and Translational Science Award, Yale SPORE in Skin Cancer

OpenAlex ID: W2768515953

FWCI: 0.49

Cites: 25

Cited by: 5

Related to: 10