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Code and Data Repository for Fast Multinomial Logistic Regression with Group Sparsity

Sheng Fu et al.

INFORMS Journal on Computing2026https://doi.org/10.1287/ijoc.2024.0796.cdarticle
AJG 3ABDC A
Weight
0.37

Abstract

The software and data in this repository are a snapshot of the software and data that were used in the research reported on in the paper Fast multinomial logistic regression with group sparsity by Sheng Fu, Shixiang Li, Kai Yu, Piao Chen, and Zhisheng Ye.

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https://doi.org/https://doi.org/10.1287/ijoc.2024.0796.cd

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@article{sheng2026,
  title        = {{Code and Data Repository for Fast Multinomial Logistic Regression with Group Sparsity}},
  author       = {Sheng Fu et al.},
  journal      = {INFORMS Journal on Computing},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1287/ijoc.2024.0796.cd},
}

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Code and Data Repository for Fast Multinomial Logistic Regression with Group Sparsity

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.