6 citations · 14 across the 4 of their papers we have counts for
5 papers
Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing
Mohammad Mahdi Kamani, Rana Forsati, James Z. Wang +1
As algorithmic decision-making systems are becoming more pervasive, it is crucial to ensure such systems do not become mechanisms of unfair discrimination on the basis of gender, r…
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks
Weilin Cong, Rana Forsati, Mahmut Kandemir +1
Sampling methods (e.g., node-wise, layer-wise, or subgraph) has become an indispensable strategy to speed up training large-scale Graph Neural Networks (GNNs). However, existing sa…
Efficient Fair Principal Component Analysis
Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati +1
It has been shown that dimension reduction methods such as PCA may be inherently prone to unfairness and treat data from different sensitive groups such as race, color, sex, etc.,…
Semi-supervised Collaborative Ranking with Push at Top
Iman Barjasteh, Rana Forsati, Abdol-Hossein Esfahanian +1
Existing collaborative ranking based recommender systems tend to perform best when there is enough observed ratings for each user and the observation is made completely at random.…
Matrix Factorization with Explicit Trust and Distrust Relationships
Rana Forsati, Mehrdad Mahdavi, Mehrnoush Shamsfard +1
With the advent of online social networks, recommender systems have became crucial for the success of many online applications/services due to their significance role in tailoring…