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09/15/2023
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
Graph Neural Networks have achieved tremendous success in modeling compl...
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06/02/2023
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms
Learning disentangled causal representations is a challenging problem th...
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03/04/2023
Achieving Counterfactual Fairness for Anomaly Detection
Ensuring fairness in anomaly detection models has received much attentio...
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12/08/2022
On Interpretable Anomaly Detection Using Causal Algorithmic Recourse
As many deep anomaly detection models have been deployed in the real-wor...
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11/11/2019
Fairness through Equality of Effort
Fair machine learning is receiving an increasing attention in machine le...
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10/20/2019
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
A recent trend of fair machine learning is to define fairness as causali...
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09/13/2018
Fairness-aware Classification: Criterion, Convexity, and Bounds
Fairness-aware classification is receiving increasing attention in the m...
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03/05/2018
On Discrimination Discovery and Removal in Ranked Data using Causal Graph
Predictive models learned from historical data are widely used to help c...
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02/28/2017
