Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"group fairness"”.
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A post-processing framework for group fairness
… may cause disparate impacts across demographic groups. For instance, models trained on data shaped by historical inequalities can propagate those biases and disadvantage protected groups: ProPublica’s analysis of the COMPAS recidivism tool showed that it disproportionately mislabeled Black …
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Data-centric Approaches for Responsible Data Science
… around responsible data science and algorithmic fairness with a strong emphasis on data-centric approaches. In this study, we firstly focus on data coverage as a data-centric approach for identifying and resolving the misrepresentation of minorities in data. We propose novel algorithms that …
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AI-in-the-loop human interventions for homelessness resource allocation
… proceeds towards developing a demographic parity group fairness criterion based intervention to improve the equity in outcomes associated with the Austin Prioritization Index Coordinated Assessment. Our findings result in the proposal of an AI-in-the-loop assistive decision system to augment and …
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Optimal Targeting under Gender Fairness
… profit, they often lack due consideration for fairness among different protected demographic groups. We investigate methods to mitigate gender disparities for both firm’s actions and benefit outcomes in the setting of offer allocations for targeted marketing campaigns. We develop and compare …
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Beyond traditional assumptions in fair machine learning
… traditional machine learning approaches to fairness in consequential decision making. After challenging the validity of these assumptions in real-world applications, we propose ways to move forward when they are violated. First, we show that group fairness criteria purely based on …
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Models and Algorithms for Performance Prediction and Course Recommendation in Higher Education
… the context of higher education. We also explore fairness concerns that might arise in a course recommendation system. We want to create models that can be used before the semester starts in order to allow the students to make any necessary adjustments in their plans. Instructors can also benefit …
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Robust data-driven optimization for dynamic and decision-dependent systems under uncertainty
… covariate shift that complicate learning, and fairness concerns arise because historical decisions may encode structural bias against certain demographic groups. To address these challenges, we propose a causal off-policy learning framework integrated with distributionally robust optimization. …