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Code and Data Repository for When Multimodal Interactions Impair Prediction: A Novel Regularized Deep Learning Strategy

Gang I. Chen & Shuaiyong Xiao

INFORMS Journal on Computing2026https://doi.org/10.1287/ijoc.2024.0794.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 When Multimodal Interactions Impair Prediction: A Novel Regularized Deep Learning Strategy by Gang Chen, Shuaiyong Xiao, Chenghong Zhang, and Huimin Zhao.

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https://doi.org/https://doi.org/10.1287/ijoc.2024.0794.cd

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@article{gang2026,
  title        = {{Code and Data Repository for When Multimodal Interactions Impair Prediction: A Novel Regularized Deep Learning Strategy}},
  author       = {Gang I. Chen & Shuaiyong Xiao},
  journal      = {INFORMS Journal on Computing},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1287/ijoc.2024.0794.cd},
}

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Code and Data Repository for When Multimodal Interactions Impair Prediction: A Novel Regularized Deep Learning Strategy

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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.