Articles with public access mandates - Julia StoyanovichLearn more
Available somewhere: 71
Measuring fairness in ranked outputs
K Yang, J Stoyanovich
Proceedings of the 29th international conference on scientific and …, 2017
Mandates: US National Science Foundation
Designing fair ranking schemes
A Asudeh, HV Jagadish, J Stoyanovich, G Das
Proceedings of the 2019 international conference on management of data, 1259 …, 2019
Mandates: US National Science Foundation, US Department of Defense
Datasynthesizer: Privacy-preserving synthetic datasets
H Ping, J Stoyanovich, B Howe
Proceedings of the 29th International Conference on Scientific and …, 2017
Mandates: US National Science Foundation, Gordon and Betty Moore Foundation
Diversity in big data: A review
M Drosou, HV Jagadish, E Pitoura, J Stoyanovich
Big data 5 (2), 73-84, 2017
Mandates: US National Science Foundation
Efficient network aware search in collaborative tagging sites
SA Yahia, M Benedikt, LVS Lakshmanan, J Stoyanovich
Proceedings of the VLDB Endowment 1 (1), 710-721, 2008
Mandates: US National Institutes of Health
A nutritional label for rankings
K Yang, J Stoyanovich, A Asudeh, B Howe, HV Jagadish, G Miklau
Proceedings of the 2018 international conference on management of data, 1773 …, 2018
Mandates: US National Science Foundation
Responsible data management
J Stoyanovich, B Howe, HV Jagadish
Proceedings of the VLDB Endowment 13 (12), 2020
Mandates: US National Science Foundation
Online set selection with fairness and diversity constraints
J Stoyanovich, K Yang, HV Jagadish
Proceedings of the EDBT Conference, 2018
Mandates: US National Science Foundation
Fairness in ranking, part i: Score-based ranking
M Zehlike, K Yang, J Stoyanovich
ACM Computing Surveys 55 (6), 1-36, 2022
Mandates: US National Science Foundation
It’s just not that simple: an empirical study of the accuracy-explainability trade-off in machine learning for public policy
A Bell, I Solano-Kamaiko, O Nov, J Stoyanovich
Proceedings of the 2022 ACM conference on fairness, accountability, and …, 2022
Mandates: US National Science Foundation
Fairness in ranking, part ii: Learning-to-rank and recommender systems
M Zehlike, K Yang, J Stoyanovich
ACM Computing Surveys 55 (6), 1-41, 2022
Mandates: US National Science Foundation
Nutritional labels for data and models
J Stoyanovich, B Howe
A Quarterly bulletin of the Computer Society of the IEEE Technical Committee …, 2019
Mandates: US National Science Foundation
Transparency, fairness, data protection, neutrality: Data management challenges in the face of new regulation
S Abiteboul, J Stoyanovich
Journal of Data and Information Quality (JDIQ) 11 (3), 1-9, 2019
Mandates: US National Science Foundation, Agence Nationale de la Recherche
Mithralabel: Flexible dataset nutritional labels for responsible data science
C Sun, A Asudeh, HV Jagadish, B Howe, J Stoyanovich
Proceedings of the 28th ACM International Conference on Information and …, 2019
Mandates: US National Science Foundation
Fairness-Aware Instrumentation of Preprocessing~ Pipelines for Machine Learning
K Yang, B Huang, J Stoyanovich, S Schelter
Workshop on Human-In-the-Loop Data Analytics (HILDA'20), 2020
Mandates: US National Science Foundation, Gordon and Betty Moore Foundation
Lightweight inspection of data preprocessing in native machine learning pipelines
S Grafberger, J Stoyanovich, S Schelter
Conference on Innovative Data Systems Research (CIDR), 2021
Mandates: US National Science Foundation
Temporal graph algebra
VZ Moffitt, J Stoyanovich
Proceedings of The 16th International Symposium on Database Programming …, 2017
Mandates: US National Science Foundation
Fides: Towards a platform for responsible data science
J Stoyanovich, B Howe, S Abiteboul, G Miklau, A Sahuguet, G Weikum
Proceedings of the 29th International Conference on Scientific and …, 2017
Mandates: US National Science Foundation, Gordon and Betty Moore Foundation
Mlinspect: A data distribution debugger for machine learning pipelines
S Grafberger, S Guha, J Stoyanovich, S Schelter
Proceedings of the 2021 International Conference on Management of Data, 2736 …, 2021
Mandates: US National Science Foundation
The imperative of interpretable machines
J Stoyanovich, JJ Van Bavel, TV West
Nature Machine Intelligence 2 (4), 197-199, 2020
Mandates: US National Science Foundation
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