Sepehr Dehdashtian

@misc{dehdashtian2024fairnessbiasmitigationcomputer,
  title = {Fairness and Bias Mitigation in Computer Vision: A Survey},
  author = {Dehdashtian*, Sepehr and He*, Ruozhen and Li, Yi and Balakrishnan, Guha and Vasconcelos, Nuno and Ordonez, Vicente and Boddeti, Vishnu Naresh},
  year = {2024},
  eprint = {2408.02464},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2408.02464},
  month = jul,
  dimensions = {true},
}

@inproceedings{birhane2024thedark,
  title = {The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models},
  author = {Birhane*, Abeba and Dehdashtian*, Sepehr and Prabhu, Vinay Uday and Boddeti, Vishnu},
  booktitle = {Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency},
  year = {2024},
  month = jul,
  dimensions = {true},
}

@inproceedings{dehdashtian2024utilityfairness,
  title = {Utility-Fairness Trade-Offs and How to Find Them},
  author = {Dehdashtian, Sepehr and Sadeghi, Bashir and Boddeti, Vishnu},
  booktitle = {Conference on Computer Vision and Pattern Recognition 2024},
  year = {2024},
  month = jun,
  dimensions = {true},
}

@inproceedings{dehdashtian2024fairvlm,
  title = {FairerCLIP: Debiasing CLIP’s Zero-Shot Predictions using Functions in RKHSs},
  author = {Dehdashtian*, Sepehr and Wang*, Lan and Boddeti, Vishnu},
  booktitle = {International Conference on Learning Representations},
  year = {2024},
  month = may,
  url = {https://openreview.net/forum?id=HXoq9EqR9e},
  dimensions = {true},
}

@article{sadeghi2022on,
  title = {On Characterizing the Trade-off in Invariant Representation Learning},
  author = {Sadeghi, Bashir and Dehdashtian, Sepehr and Boddeti, Vishnu},
  journal = {Transactions on Machine Learning Research},
  issn = {2835-8856},
  year = {2022},
  url = {https://openreview.net/forum?id=3gfpBR1ncr},
  note = {Featured Certification},
  dimensions = {true},
}