Mar 20, 2023 · In this paper, we design a fair graph filter that can be employed in a versatile manner for graph-based learning tasks.
Jan 10, 2024 · Our idea is to introduce predesigned graph filters within an ML pipeline to reduce a novel unsupervised bias measure, namely the correlation ...
Jul 3, 2024 · The approach in [32] is to “edit” the input graph signal for fairness enhancement and does not focus on optimal filter design. Overall, our ...
The design of the proposed filter is based on a bias analysis and its optimality in mitigating bias compared to its fairness-agnostic counterpart is established ...
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Oct 22, 2024 · Our idea is to introduce predesigned graph filters within an ML pipeline to reduce a novel unsupervised bias measure, namely the correlation ...
This paper deals with the problem of distributed H∞ consensus filtering for a continuous-time Itô-type stochastic system with Wiener process disturbances ...
Nov 5, 2024 · This paper examines the issue of fairness in the estimation of graphical models (GMs), particularly Gaussian, Covariance, and Ising models.
Jun 19, 2024 · A novel algorithm, FairGAT, which leverages a fairness-aware attention design, is developed based on the theoretical findings.
Oct 23, 2024 · We propose FairDgcl, a dynamic graph adversarial contrastive learning framework aiming at improving fairness in recommender system.
