ML Anthology

Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps

Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang
IJCAI 2017 pp. 3315-3321
doi:10.24963/IJCAI.2017/463 /ijcai/2017/ye2017ijcai-learning/
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Cite

Text

Ye et al. "Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/463

Markdown

[Ye et al. "Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/ye2017ijcai-learning/) doi:10.24963/IJCAI.2017/463

BibTeX

@inproceedings{ye2017ijcai-learning,
  title     = {{Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps}},
  author    = {Ye, Han-Jia and Zhan, De-Chuan and Si, Xue-Min and Jiang, Yuan},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {3315-3321},
  doi       = {10.24963/IJCAI.2017/463},
  url       = {https://mlanthology.org/ijcai/2017/ye2017ijcai-learning/}
}