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Publication search results
found 53 matches
- 2023
- Joachim Baumann, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli:
An Open-Source Toolkit to Generate Biased Datasets. EWAF 2023 - Joachim Baumann, Anikó Hannák, Christoph Heitz:
Fair Machine Learning Through Post-processing: The Case of Predictive Parity. EWAF 2023 - Joachim Baumann, Corinna Hertweck, Michele Loi, Christoph Heitz:
Unification, Extension, and Interpretation of Group Fairness Metrics for ML-Based Decision-Making. EWAF 2023 - Andreas Nikolaos Athanasopoulos, Amanda Belfrage, David Berg Marklund, Christos Dimitrakakis:
Approximate Inference for the Bayesian Fairness Framework. EWAF 2023 - Ahmet Bilal Aytekin:
Algorithmic Bias in the Context of European Union Anti-Discrimination Directives. EWAF 2023 - Sander Beckers, Hana Chockler, Joseph Y. Halpern:
A Causal Analysis of Harm. EWAF 2023 - Marcello Di Bello, Nicolò Cangiotti, Michele Loi:
Classification Parity, Causal Equal Protection and Algorithmic Fairness. EWAF 2023 - Giorgian Borca-Tasciuc, Xingzhi Guo, Stanley Bak, Steven Skiena:
Provable Fairness for Neural Network Models Using Formal Verification. EWAF 2023 - Lou Therese Brandner, Philipp Mahlow, Anna Wilken, Annika Wölke, Hazar Harmouch, Simon David Hirsbrunner:
How Data Quality Determines AI Fairness: The Case of Automated Interviewing. EWAF 2023 - Adrian Byrne, Ivan Caffrey, Quan Le:
Towards a Framework for the Global Assessment of Sensitive Attribute Bias Within Binary Classification Algorithms. EWAF 2023 - Eugenia Cacciatori, Enzo Fenoglio, Emre Kazim:
Living with Opaque Technologies: Insights for AI from Digital Simulations. EWAF 2023 - Gabriele Carovano, Alexander Meinke:
Improving Fairness and Cybersecurity in the Artificial Intelligence Act. EWAF 2023 - Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel:
The Case for Correctability in Fair Machine Learning. EWAF 2023 - Matteo Fabbri:
Social Influence for Societal Interest: A Pro-Ethical Framework for Improving Human Decision-Making Through Multi-Stakeholder Recommender Systems. EWAF 2023 - Matteo Fabbri:
From Digital Nudging to Users' Self-Determination: Explainability as a Framework for the Effective Implementation of the Transparency Requirements for Recommender Systems Set by the Digital Services Act of the European Union. EWAF 2023 - Alessandro Fabris, Fabio Giachelle, Alberto Piva, Gianmaria Silvello, Gian Antonio Susto:
A Search Engine for Algorithmic Fairness Datasets. EWAF 2023 - Andrea Ferrario:
Through the Sands of Time: A Reliabilistic Account of Justified Credence in the Trustworthiness of AI Systems. EWAF 2023 - Siamak Ghodsi, Eirini Ntoutsi:
Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy. EWAF 2023 - Sofie Goethals, David Martens, Toon Calders:
Explainability Methods to Detect and Measure Discrimination in Machine Learning Models. EWAF 2023 - Sakina Hansen, Joshua R. Loftus:
Model-Agnostic Auditing: A Lost Cause? EWAF 2023 - Corinna Hertweck, Joachim Baumann, Michele Loi, Christoph Heitz:
FairnessLab: A Consequence-Sensitive Bias Audit and Mitigation Toolkit. EWAF 2023 - Lukas Hondrich, Hannah Ruschemeier:
Addressing Automation Bias through Verifiability. EWAF 2023 - Sofia Jaime, Christoph Kern:
Ethnic Classifications in Algorithmic Decision-Making Processes. EWAF 2023 - Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser:
Breaking Bias: How Optimal Transport Can Help to Tackle Gender Biases in NLP Based Job Recommendation Systems? EWAF 2023 - Fanny Jourdan, Ronan Pons, Nicholas Asher, Jean-Michel Loubes, Laurent Risser:
Is a Fairness Metric Score Enough to Assess Discrimination Biases in Machine Learning? EWAF 2023 - Christoph Kern, Ruben L. Bach, Hannah Mautner, Frauke Kreuter:
When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes. EWAF 2023 - Bogdan Kulynych, Hsiang Hsu, Carmela Troncoso, Flávio P. Calmon:
Arbitrary Decisions Are a Hidden Cost of Differentially Private Training. EWAF 2023 - Joshua R. Loftus:
It's About Time: Counterfactual Fairness and Temporal Depth. EWAF 2023 - Alex Loosley, Amrollah Seifoddini, Alessandro Canopoli, Meike Zehlike:
Body Measurement Prediction Fairness. EWAF 2023 - Jan-Laurin Müller:
Fairness in Machine Learning as 'Algorithmic Positive Action'. EWAF 2023
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