Discrimination- and privacy-aware patterns

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Discrimination Aware Decision Tree Learning

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Decision Theory for Discrimination-Aware Classification

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When do data mining results violate privacy?

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Discrimination and Privacy in the Information Society: Data Mining and Profiling in Large Databases

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Quantifying explainable discrimination and removing illegal discrimination in automated decision making

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Differential identifiability

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Crowd-Blending Privacy

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Generalization-based privacy preservation and discrimination prevention in data publishing and mining

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Integrating induction and deduction for finding evidence of discrimination

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Rule Protection for Indirect Discrimination Prevention in Data Mining

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Better decision support through exploratory discrimination-aware data mining: foundations and empirical evidence

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Injecting Discrimination and Privacy Awareness Into Pattern Discovery

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Mining frequent patterns with differential privacy

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A Study on the Impact of Data Anonymization on Anti-discrimination

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The Discovery of Discrimination

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SENSITIVITY-INDEPENDENT DIFFERENTIAL PRIVACY VIA PRIOR KNOWLEDGE REFINEMENT

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Interpretability of deep learning models: A survey of results

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Learning Adversarially Fair and Transferable RepresentationsPreprint

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Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining

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Fairness in Machine Learning

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Measuring discrimination in algorithmic decision making

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Big Data and discrimination: perils, promises and solutions. A systematic review

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The Internet of People (IoP): A new wave in pervasive mobile computing

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What We Can't Measure, We Can't Understand: Challenges to Demographic Data Procurement in the Pursuit of Fairness

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Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and unfairness within data management and analytics systems

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Big Data Security and Privacy

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One-Network Adversarial Fairness

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Exposing the probabilistic causal structure of discrimination

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FAHT: An Adaptive Fairness-aware Decision Tree Classifier

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The Ethics of Cybersecurity

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Big Data - Security and Privacy

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Differentially Private and Fair Classification via Calibrated Functional Mechanism

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Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming

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Mitigating Bias in Set Selection with Noisy Protected Attributes

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Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent

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Self-regulatory information sharing in participatory social sensing

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Fair Meta-Learning For Few-Shot Classification

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Rank-Based Multi-task Learning for Fair Regression

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Implications of Data Anonymization on the Statistical Evidence of Disparity

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On Discrimination Discovery Using Causal Networks

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FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning

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Big Data Research in Italy: A Perspective

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"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of FairnessPreprint

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Generating Fair Universal Representations Using Adversarial Models

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Image fairness in deep learning: problems, models, and challenges

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Privacy-Preserving Technologies

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Understanding Disparate Effects of Membership Inference Attacks and their Countermeasures

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A literature review on artificial intelligence and ethics in online learning

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Censored and Fair Universal Representations using Generative Adversarial Models

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Fair Transfer Learning with Factor Variational Auto-Encoder

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Evaluating the disclosure risk of anonymized documents via a machine learning-based re-identification attack

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Mining social interactions in privacy-preserving temporal networks

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Using Loglinear Model for Discrimination Discovery and Prevention

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Model-Agnostic Causal Embedding Learning for Counterfactually Group-Fair Recommendation

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Privacy and Fairness in Machine Learning: A Survey

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On Fairness-Aware Learning for Non-discriminative Decision-Making

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Flexible and Adaptive Fairness-aware Learning in Non-stationary Data Streams

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FAC-fed: Federated adaptation for fairness and concept drift aware stream classification

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Investigating Trade-offs in Utility, Fairness and Differential Privacy in Neural NetworksPreprint

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Disparate Vulnerability in Link Inference Attacks against Graph Neural Networks

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Using Balancing Terms to Avoid Discrimination in Classification

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