Artikelen met mandaten voor openbare toegang - Navid RekabsazMeer informatie
Ergens beschikbaar: 32
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers
N Rekabsaz, S Kopeinik, M Schedl
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
Mandaten: European Commission
Analyzing item popularity bias of music recommender systems: are different genders equally affected?
O Lesota, A Melchiorre, N Rekabsaz, S Brandl, D Kowald, E Lex, ...
Proceedings of the 15th ACM conference on recommender systems, 601-606, 2021
Mandaten: Austrian Science Fund, European Commission
Exploration of a threshold for similarity based on uncertainty in word embedding
N Rekabsaz, M Lupu, A Hanbury
Advances in Information Retrieval: 39th European Conference on IR Research …, 2017
Mandaten: Austrian Science Fund
LFM-2b: A dataset of enriched music listening events for recommender systems research and fairness analysis
M Schedl, S Brandl, O Lesota, E Parada-Cabaleiro, D Penz, N Rekabsaz
Proceedings of the 2022 Conference on Human Information Interaction and …, 2022
Mandaten: Austrian Science Fund
Tripclick: the log files of a large health web search engine
N Rekabsaz, O Lesota, M Schedl, J Brassey, C Eickhoff
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
Mandaten: US National Science Foundation
Unlearning protected user attributes in recommendations with adversarial training
C Ganhör, D Penz, N Rekabsaz, O Lesota, M Schedl
Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022
Mandaten: Austrian Science Fund
On the effect of low-frequency terms on neural-IR models
S Hofstätter, N Rekabsaz, C Eickhoff, A Hanbury
Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019
Mandaten: US Department of Defense, US Office of the Director of National Intelligence
Mitigating bias in search results through contextual document reranking and neutrality regularization
G Zerveas, N Rekabsaz, D Cohen, C Eickhoff
Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022
Mandaten: US National Science Foundation
Word embedding causes topic shifting; exploit global context!
N Rekabsaz, M Lupu, A Hanbury, H Zamani
Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017
Mandaten: Austrian Science Fund
Grep-biasir: A dataset for investigating gender representation bias in information retrieval results
K Krieg, E Parada-Cabaleiro, G Medicus, O Lesota, M Schedl, ...
Proceedings of the 2023 Conference on Human Information Interaction and …, 2023
Mandaten: Austrian Science Fund
Generalizing translation models in the probabilistic relevance framework
N Rekabsaz, M Lupu, A Hanbury, G Zuccon
Proceedings of the 25th ACM international on conference on information and …, 2016
Mandaten: Austrian Science Fund
Not all relevance scores are equal: Efficient uncertainty and calibration modeling for deep retrieval models
D Cohen, B Mitra, O Lesota, N Rekabsaz, C Eickhoff
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
Mandaten: US National Science Foundation, US Office of the Director of National …
Protomf: Prototype-based matrix factorization for effective and explainable recommendations
AB Melchiorre, N Rekabsaz, C Ganhör, M Schedl
Proceedings of the 16th ACM Conference on Recommender Systems, 246-256, 2022
Mandaten: Austrian Science Fund
Parameter-efficient modularised bias mitigation via AdapterFusion
D Kumar, O Lesota, G Zerveas, D Cohen, C Eickhoff, M Schedl, ...
arXiv preprint arXiv:2302.06321, 2023
Mandaten: Austrian Science Fund
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements?
K Krieg, E Parada-Cabaleiro, M Schedl, N Rekabsaz
International Workshop on Algorithmic Bias in Search and Recommendation, 104-116, 2022
Mandaten: Austrian Science Fund
A modern perspective on query likelihood with deep generative retrieval models
O Lesota, N Rekabsaz, D Cohen, KA Grasserbauer, C Eickhoff, M Schedl
Proceedings of the 2021 ACM SIGIR International Conference on Theory of …, 2021
Mandaten: US National Science Foundation
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization.
O Lesota, S Brandl, M Wenzel, AB Melchiorre, E Lex, N Rekabsaz, ...
MORS@ RecSys, 2022
Mandaten: Austrian Science Fund
Show me a" Male Nurse"! How Gender Bias is Reflected in the Query Formulation of Search Engine Users
S Kopeinik, M Mara, L Ratz, K Krieg, M Schedl, N Rekabsaz
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems …, 2023
Mandaten: Austrian Science Fund, European Commission
Multiperspective and multidisciplinary treatment of fairness in recommender systems research
M Schedl, N Rekabsaz, E Lex, T Grosz, E Greif
Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation …, 2022
Mandaten: Austrian Science Fund
Fairness of recommender systems in the recruitment domain: an analysis from technical and legal perspectives
D Kumar, T Grosz, N Rekabsaz, E Greif, M Schedl
Frontiers in big Data 6, 1245198, 2023
Mandaten: Austrian Science Fund
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