Divide-and-conquer random sketched kernel ridge regression for large-scale data analysis

Jongkyeong Kang; Myoungshic Jhun

doi:10.7465/jkdi.2020.31.1.15

ScienceGate Book Chapters

JOURNAL ARTICLE

Divide-and-conquer random sketched kernel ridge regression for large-scale data analysis

Jongkyeong Kang Myoungshic Jhun

Year: 2020 Journal: Journal of the Korean Data and Information Science Society Vol: 31 (1)Pages: 15-23 Publisher: The Korean Data and Information Science Society (KDISS)

DOI: 10.7465/jkdi.2020.31.1.15

Get Full-Text PDF Get Analytical Report

Keywords:

Divide and conquer algorithms Ridge Scale (ratio) Computer science Kernel (algebra) Regression Kernel regression Statistics Mathematics Algorithm Geography Cartography Combinatorics

Metrics

Cited By

0.21

FWCI (Field Weighted Citation Impact)

Refs

0.47

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Divide-and-conquer random sketched kernel ridge regression for large-scale data analysis

Metrics

Citation History

Topics

Related Documents

Divide and conquer kernel ridge regression

Sketched ridge regression

Distributed Generalized Cross-Validation for Divide-and-Conquer Kernel Ridge Regression and Its Asymptotic Optimality

Divide and conquer kernel quantile regression for massive dataset

Large-scale random features for kernel regression