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Abdel Djalil Sad Saoud

2 accepted papers

2026

BEYOND MAPPING : DOMAIN-INVARIANT REPRESENTATIONS VIA SPECTRAL EMBEDDING OF OPTIMAL TRANSPORT PLANS

ICASSP 2026poster

Distributional shifts between training and inference time data remain a central challenge in machine learning, often leading to poor performance. It motivated the study of principled approaches for domain alignment, such as optimal transport based unsupervised domain adaptation, that relies on appro…

Cited by 0SourcePDFScholar
2026

Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models

CVPR 2026

The issue of algorithmic biases in deep learning has led to the development of various debiasing techniques, many of which perform complex training procedures or dataset manipulation. However, an intriguing question arises: is it possible to extract fair and bias-agnostic subnetworks from standard v

Cited by 0SourcecodeScholar