publications

2024

1. Preprint

   

   Fairness and Bias Mitigation in Computer Vision: A Survey

   Sepehr Dehdashtian*, Ruozhen He*, Yi Li, Guha Balakrishnan, Nuno Vasconcelos, Vicente Ordonez, and Vishnu Naresh Boddeti

   Jul 2024

   Bib PDF

   @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},
   }

2. FAccT’24

   

   The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models

   Abeba Birhane*, Sepehr Dehdashtian*, Vinay Uday Prabhu, and Vishnu Boddeti

   In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency , Jul 2024

   Bib PDF Code Poster

   @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},
   }

3. CVPR’24

   

   Utility-Fairness Trade-Offs and How to Find Them

   Sepehr Dehdashtian, Bashir Sadeghi, and Vishnu Boddeti

   In Conference on Computer Vision and Pattern Recognition 2024 , Jun 2024

   Bib PDF Code Poster Slides Website

   @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},
   }

4. ICLR’24

   

   FairerCLIP: Debiasing CLIP’s Zero-Shot Predictions using Functions in RKHSs

   Sepehr Dehdashtian*, Lan Wang*, and Vishnu Boddeti

   In International Conference on Learning Representations , May 2024

   Bib PDF Code Poster Slides Website

   @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},
   }

2022

1. TMLR

   

   On Characterizing the Trade-off in Invariant Representation Learning

   Bashir Sadeghi, Sepehr Dehdashtian, and Vishnu Boddeti

   Transactions on Machine Learning Research, May 2022

   Featured Certification

   Bib HTML PDF

   @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},
   }

2021

1. WCL

   

   Deep-Learning-Based Blind Recognition of Channel Code Parameters Over Candidate Sets Under AWGN and Multi-Path Fading Conditions

   Sepehr Dehdashtian, Matin Hashemi, and Saber Salehkaleybar

   IEEE Wireless Communications Letters, May 2021

   Bib HTML PDF

   @article{9344644,
     author = {Dehdashtian, Sepehr and Hashemi, Matin and Salehkaleybar, Saber},
     journal = {IEEE Wireless Communications Letters},
     title = {Deep-Learning-Based Blind Recognition of Channel Code Parameters Over Candidate Sets Under AWGN and Multi-Path Fading Conditions},
     year = {2021},
     volume = {10},
     number = {5},
     pages = {1041-1045},
     dimensions = {true},
   }