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08/23/2023
Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems
In recommendation literature, explainability and fairness are becoming t...
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08/22/2023
(Un)fair Exposure in Deep Face Rankings at a Distance
Law enforcement regularly faces the challenge of ranking suspects from t...
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04/12/2023
GNNUERS: Fairness Explanation in GNNs for Recommendation via Counterfactual Reasoning
In recent years, personalization research has been delving into issues o...
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01/14/2023
Knowledge is Power, Understanding is Impact: Utility and Beyond Goals, Explanation Quality, and Fairness in Path Reasoning Recommendation
Path reasoning is a notable recommendation approach that models high-ord...
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12/20/2022
Protected Attributes Tell Us Who, Behavior Tells Us How: A Comparison of Demographic and Behavioral Oversampling for Fair Student Success Modeling
Algorithms deployed in education can shape the learning experience and s...
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12/17/2022
Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design
Deep learning models for learning analytics have become increasingly pop...
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12/16/2022
Do Not Trust a Model Because It is Confident: Uncovering and Characterizing Unknown Unknowns to Student Success Predictors in Online-Based Learning
Student success models might be prone to develop weak spots, i.e., examp...
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12/02/2022
Ripple: Concept-Based Interpretation for Raw Time Series Models in Education
Time series is the most prevalent form of input data for educational pre...
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09/30/2022
The More Secure, The Less Equally Usable: Gender and Ethnicity (Un)fairness of Deep Face Recognition along Security Thresholds
Face biometrics are playing a key role in making modern smart city appli...
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09/11/2022
Reinforcement Recommendation Reasoning through Knowledge Graphs for Explanation Path Quality
Numerous Knowledge Graphs (KGs) are being created to make recommender sy...
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08/23/2022
Explaining Bias in Deep Face Recognition via Image Characteristics
In this paper, we propose a novel explanatory framework aimed to provide...
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07/04/2022
Generalisable Methods for Early Prediction in Interactive Simulations for Education
Interactive simulations allow students to discover the underlying princi...
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07/01/2022
Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs
Neural networks are ubiquitous in applied machine learning for education...
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06/23/2022
Experts' View on Challenges and Needs for Fairness in Artificial Intelligence for Education
In recent years, there has been a stimulating discussion on how artifici...
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04/25/2022
Meta Transfer Learning for Early Success Prediction in MOOCs
Despite the increasing popularity of massive open online courses (MOOCs)...
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04/24/2022
Dictionary Attacks on Speaker Verification
In this paper, we propose dictionary attacks against speaker verificatio...
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04/24/2022
Regulating Group Exposure for Item Providers in Recommendation
Engaging all content providers, including newcomers or minority demograp...
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04/24/2022
Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations
Existing explainable recommender systems have mainly modeled relationshi...
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03/30/2022
Robust Reputation Independence in Ranking Systems for Multiple Sensitive Attributes
Ranking systems have an unprecedented influence on how and what informat...
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01/21/2022
Consumer Fairness in Recommender Systems: Contextualizing Definitions and Mitigations
Enabling non-discrimination for end-users of recommender systems by intr...
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04/29/2021
Improving Fairness in Speaker Recognition
The human voice conveys unique characteristics of an individual, making ...
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06/07/2020
Equality of Learning Opportunity in Personalized Recommendations
Online educational platforms are promising to play a primary role in med...
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06/07/2020
Interplay between Upsampling and Regularization for Provider Fairness in Recommender Systems
Considering the impact of recommendations on item providers is one of th...
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06/07/2020
Connecting User and Item Perspectives in Popularity Debiasing for Collaborative Recommendation
Recommender systems learn from historical data that is often non-uniform...
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05/14/2020