An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems

677 indexed citations
published 2009
Journal
National University of Singapore

In The Last Decade

doi.org/w50235800 →

Countries where authors are citing An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems

Specialization
Citations

This map shows the geographic impact of An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems more than expected).

Fields of papers citing An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems.

About An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems

This paper, published in 2009, received 677 indexed citations . Written by Kim-Chuan Toh and Sangwoon Yun covering the research area of Aerospace Engineering, Artificial Intelligence and Computational Mechanics. It is primarily cited by scholars working on Computational Mechanics (478 citations), Computer Vision and Pattern Recognition (340 citations) and Signal Processing (158 citations). Published in National University of Singapore.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/w50235800.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026