Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning

Cite

Text

Zhang et al. "Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I9.26324

Markdown

[Zhang et al. "Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/zhang2023aaai-denoising/) doi:10.1609/AAAI.V37I9.26324

BibTeX

@inproceedings{zhang2023aaai-denoising,
  title     = {{Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning}},
  author    = {Zhang, Chenkang and Luo, Lei and Gu, Bin},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {11183-11191},
  doi       = {10.1609/AAAI.V37I9.26324},
  url       = {https://mlanthology.org/aaai/2023/zhang2023aaai-denoising/}
}