De-Singularity Subgradient for the Q-Th-Powered Lₚ-Norm Weber Location Problem

Zhao-Rong Lai, Xiaotian Wu, Liangda Fang, Ziliang Chen, Cheng Li

AAAI 2025 pp. 18026-18034

doi:10.1609/AAAI.V39I17.33983 /aaai/2025/lai2025aaai-de/

Abstract

The Weber location problem is widely used in several artificial intelligence scenarios. However, the gradient of the objective does not exist at a considerable set of singular points. Recently, a de-singularity subgradient method has been proposed to fix this problem, but it can only handle the q-th-powered l_2-norm case (1

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Text

Lai et al. "De-Singularity Subgradient for the Q-Th-Powered Lₚ-Norm Weber Location Problem." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I17.33983

Markdown

[Lai et al. "De-Singularity Subgradient for the Q-Th-Powered Lₚ-Norm Weber Location Problem." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/lai2025aaai-de/) doi:10.1609/AAAI.V39I17.33983

BibTeX

@inproceedings{lai2025aaai-de,
  title     = {{De-Singularity Subgradient for the Q-Th-Powered Lₚ-Norm Weber Location Problem}},
  author    = {Lai, Zhao-Rong and Wu, Xiaotian and Fang, Liangda and Chen, Ziliang and Li, Cheng},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {18026-18034},
  doi       = {10.1609/AAAI.V39I17.33983},
  url       = {https://mlanthology.org/aaai/2025/lai2025aaai-de/}
}