Artykuły w czasopismach na temat „Fairness-Accuracy trade-Off”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Sprawdź 38 najlepszych artykułów w czasopismach naukowych na temat „Fairness-Accuracy trade-Off”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Przeglądaj artykuły w czasopismach z różnych dziedzin i twórz odpowiednie bibliografie.
Jang, Taeuk, Pengyi Shi i Xiaoqian Wang. "Group-Aware Threshold Adaptation for Fair Classification". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 6 (28.06.2022): 6988–95. http://dx.doi.org/10.1609/aaai.v36i6.20657.
Pełny tekst źródłaLangenberg, Anna, Shih-Chi Ma, Tatiana Ermakova i Benjamin Fabian. "Formal Group Fairness and Accuracy in Automated Decision Making". Mathematics 11, nr 8 (7.04.2023): 1771. http://dx.doi.org/10.3390/math11081771.
Pełny tekst źródłaTae, Ki Hyun, Hantian Zhang, Jaeyoung Park, Kexin Rong i Steven Euijong Whang. "Falcon: Fair Active Learning Using Multi-Armed Bandits". Proceedings of the VLDB Endowment 17, nr 5 (styczeń 2024): 952–65. http://dx.doi.org/10.14778/3641204.3641207.
Pełny tekst źródłaBadar, Maryam, Sandipan Sikdar, Wolfgang Nejdl i Marco Fisichella. "FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 10 (24.03.2024): 10962–70. http://dx.doi.org/10.1609/aaai.v38i10.28971.
Pełny tekst źródłaLi, Xuran, Peng Wu i Jing Su. "Accurate Fairness: Improving Individual Fairness without Trading Accuracy". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 12 (26.06.2023): 14312–20. http://dx.doi.org/10.1609/aaai.v37i12.26674.
Pełny tekst źródłaSilvia, Chiappa, Jiang Ray, Stepleton Tom, Pacchiano Aldo, Jiang Heinrich i Aslanides John. "A General Approach to Fairness with Optimal Transport". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 04 (3.04.2020): 3633–40. http://dx.doi.org/10.1609/aaai.v34i04.5771.
Pełny tekst źródłaPinzón, Carlos, Catuscia Palamidessi, Pablo Piantanida i Frank Valencia. "On the Impossibility of Non-trivial Accuracy in Presence of Fairness Constraints". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 7 (28.06.2022): 7993–8000. http://dx.doi.org/10.1609/aaai.v36i7.20770.
Pełny tekst źródłaSingh, Arashdeep, Jashandeep Singh, Ariba Khan i Amar Gupta. "Developing a Novel Fair-Loan Classifier through a Multi-Sensitive Debiasing Pipeline: DualFair". Machine Learning and Knowledge Extraction 4, nr 1 (12.03.2022): 240–53. http://dx.doi.org/10.3390/make4010011.
Pełny tekst źródłaGitiaux, Xavier, i Huzefa Rangwala. "Fair Representations by Compression". Proceedings of the AAAI Conference on Artificial Intelligence 35, nr 13 (18.05.2021): 11506–15. http://dx.doi.org/10.1609/aaai.v35i13.17370.
Pełny tekst źródłaGao, Shiqi, Xianxian Li, Zhenkui Shi, Peng Liu i Chunpei Li. "Towards Fair and Decentralized Federated Learning System for Gradient Boosting Decision Trees". Security and Communication Networks 2022 (2.08.2022): 1–18. http://dx.doi.org/10.1155/2022/4202084.
Pełny tekst źródłaPan, Chenglu, Jiarong Xu, Yue Yu, Ziqi Yang, Qingbiao Wu, Chunping Wang, Lei Chen i Yang Yang. "Towards Fair Graph Federated Learning via Incentive Mechanisms". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 13 (24.03.2024): 14499–507. http://dx.doi.org/10.1609/aaai.v38i13.29365.
Pełny tekst źródłaLi, Yanying, Xiuling Wang, Yue Ning i Hui Wang. "FairLP: Towards Fair Link Prediction on Social Network Graphs". Proceedings of the International AAAI Conference on Web and Social Media 16 (31.05.2022): 628–39. http://dx.doi.org/10.1609/icwsm.v16i1.19321.
Pełny tekst źródłaZeng, Ziqian, Rashidul Islam, Kamrun Naher Keya, James Foulds, Yangqiu Song i Shimei Pan. "Fair Representation Learning for Heterogeneous Information Networks". Proceedings of the International AAAI Conference on Web and Social Media 15 (22.05.2021): 877–87. http://dx.doi.org/10.1609/icwsm.v15i1.18111.
Pełny tekst źródłaSun, Ying, Fariborz Haghighat i Benjamin C. M. Fung. "Trade-off between accuracy and fairness of data-driven building and indoor environment models: A comparative study of pre-processing methods". Energy 239 (styczeń 2022): 122273. http://dx.doi.org/10.1016/j.energy.2021.122273.
Pełny tekst źródłaSun, Ying, Fariborz Haghighat i Benjamin C. M. Fung. "Trade-off between accuracy and fairness of data-driven building and indoor environment models: A comparative study of pre-processing methods". Energy 239 (styczeń 2022): 122273. http://dx.doi.org/10.1016/j.energy.2021.122273.
Pełny tekst źródłaLi, Qin, Zhou, Cheng, Zhang i Ai. "Intelligent Rapid Adaptive Offloading Algorithm for Computational Services in Dynamic Internet of Things System". Sensors 19, nr 15 (4.08.2019): 3423. http://dx.doi.org/10.3390/s19153423.
Pełny tekst źródłaHERBORDT, MARTIN C., i CHARLES C. WEEMS. "ENPASSANT: AN ENVIRONMENT FOR EVALUATING MASSIVELY PARALLEL ARRAY ARCHITECTURES FOR SPATIALLY MAPPED APPLICATIONS". International Journal of Pattern Recognition and Artificial Intelligence 09, nr 02 (kwiecień 1995): 175–200. http://dx.doi.org/10.1142/s0218001495000109.
Pełny tekst źródłaKieslich, Kimon, Birte Keller i Christopher Starke. "Artificial intelligence ethics by design. Evaluating public perception on the importance of ethical design principles of artificial intelligence". Big Data & Society 9, nr 1 (styczeń 2022): 205395172210929. http://dx.doi.org/10.1177/20539517221092956.
Pełny tekst źródłaCosta, Diogo, Miguel Costa i Sandro Pinto. "Train Me If You Can: Decentralized Learning on the Deep Edge". Applied Sciences 12, nr 9 (6.05.2022): 4653. http://dx.doi.org/10.3390/app12094653.
Pełny tekst źródłaSchwartz, Jessica M., Maureen George, Sarah Collins Rossetti, Patricia C. Dykes, Simon R. Minshall, Eugene Lucas i Kenrick D. Cato. "Factors Influencing Clinician Trust in Predictive Clinical Decision Support Systems for In-Hospital Deterioration: Qualitative Descriptive Study". JMIR Human Factors 9, nr 2 (12.05.2022): e33960. http://dx.doi.org/10.2196/33960.
Pełny tekst źródłaLi, Jingyang, i Guoqiang Li. "The Triangular Trade-off between Robustness, Accuracy and Fairness in Deep Neural Networks: A Survey". ACM Computing Surveys, 12.02.2024. http://dx.doi.org/10.1145/3645088.
Pełny tekst źródłaTalbert, Douglas A., Katherine L. Phillips, Katherine E. Brown i Steve Talbert. "Assessing and Addressing Model Trustworthiness Trade-offs in Trauma Triage". International Journal on Artificial Intelligence Tools 33, nr 03 (25.04.2024). http://dx.doi.org/10.1142/s0218213024600078.
Pełny tekst źródłaChen, Zhenpeng, Jie M. Zhang, Federica Sarro i Mark Harman. "A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers". ACM Transactions on Software Engineering and Methodology, 9.02.2023. http://dx.doi.org/10.1145/3583561.
Pełny tekst źródłaBuijsman, Stefan. "Navigating fairness measures and trade-offs". AI and Ethics, 17.07.2023. http://dx.doi.org/10.1007/s43681-023-00318-0.
Pełny tekst źródłaWei, Chen, Kui Xu, Zhexian Shen, Xiaochen Xia, Wei Xie i Chunguo Li. "Location-aided uplink transmission for user-centric cell-free massive MIMO systems: a fairness priority perspective". EURASIP Journal on Wireless Communications and Networking 2022, nr 1 (11.09.2022). http://dx.doi.org/10.1186/s13638-022-02171-x.
Pełny tekst źródłaDuricic, Tomislav, Dominik Kowald, Emanuel Lacic i Elisabeth Lex. "Beyond-accuracy: a review on diversity, serendipity, and fairness in recommender systems based on graph neural networks". Frontiers in Big Data 6 (19.12.2023). http://dx.doi.org/10.3389/fdata.2023.1251072.
Pełny tekst źródłaRueda, Jon, Janet Delgado Rodríguez, Iris Parra Jounou, Joaquín Hortal-Carmona, Txetxu Ausín i David Rodríguez-Arias. "“Just” accuracy? Procedural fairness demands explainability in AI-based medical resource allocations". AI & SOCIETY, 21.12.2022. http://dx.doi.org/10.1007/s00146-022-01614-9.
Pełny tekst źródłaOh, Hyeji, i Chulyun Kim. "Fairness-aware recommendation with meta learning". Scientific Reports 14, nr 1 (2.05.2024). http://dx.doi.org/10.1038/s41598-024-60808-x.
Pełny tekst źródłaZhang, Tao, Tianqing Zhu, Mengde Han, Fengwen Chen, Jing Li, Wanlei Zhou i Philip S. Yu. "Fairness in graph-based semi-supervised learning". Knowledge and Information Systems, 1.10.2022. http://dx.doi.org/10.1007/s10115-022-01738-w.
Pełny tekst źródłaLoi, Michele, i Markus Christen. "Choosing how to discriminate: navigating ethical trade-offs in fair algorithmic design for the insurance sector". Philosophy & Technology, 13.03.2021. http://dx.doi.org/10.1007/s13347-021-00444-9.
Pełny tekst źródłaScher, Sebastian, Simone Kopeinik, Andreas Trügler i Dominik Kowald. "Modelling the long-term fairness dynamics of data-driven targeted help on job seekers". Scientific Reports 13, nr 1 (31.01.2023). http://dx.doi.org/10.1038/s41598-023-28874-9.
Pełny tekst źródłaMüllner, Peter, Elisabeth Lex, Markus Schedl i Dominik Kowald. "Differential privacy in collaborative filtering recommender systems: a review". Frontiers in Big Data 6 (12.10.2023). http://dx.doi.org/10.3389/fdata.2023.1249997.
Pełny tekst źródłaIslam, Sheikh Rabiul, Ingrid Russell, William Eberle, Douglas Talbert i Md Golam Moula Mehedi Hasan. "Advances in Explainable, Fair, and Trustworthy AI". International Journal on Artificial Intelligence Tools 33, nr 03 (22.04.2024). http://dx.doi.org/10.1142/s0218213024030015.
Pełny tekst źródłaPal, Manjish, Subham Pokhriyal, Sandipan Sikdar i Niloy Ganguly. "Ensuring generalized fairness in batch classification". Scientific Reports 13, nr 1 (2.11.2023). http://dx.doi.org/10.1038/s41598-023-45943-1.
Pełny tekst źródłaShanklin, Robert, Michele Samorani, Shannon Harris i Michael A. Santoro. "Ethical Redress of Racial Inequities in AI: Lessons from Decoupling Machine Learning from Optimization in Medical Appointment Scheduling". Philosophy & Technology 35, nr 4 (20.10.2022). http://dx.doi.org/10.1007/s13347-022-00590-8.
Pełny tekst źródłaSzepannek, Gero, i Karsten Lübke. "Facing the Challenges of Developing Fair Risk Scoring Models". Frontiers in Artificial Intelligence 4 (14.10.2021). http://dx.doi.org/10.3389/frai.2021.681915.
Pełny tekst źródłaCortés-Andrés, Jordi, Gustau Camps-Valls, Sebastian Sippel, Eniko Melinda Székely, Dino Sejdinovic, Emiliano Díaz, Adrián Pérez-Suay, Zhu Li, Miguel D. Mahecha i Markus Reichstein. "Physics-aware nonparametric regression models for Earth data analysis". Environmental Research Letters, 14.04.2022. http://dx.doi.org/10.1088/1748-9326/ac6762.
Pełny tekst źródłaPham, Diem, Binh Tran, Su Nguyen, Damminda Alahakoon i Mengjie Zhang. "Fairness optimisation with multi-objective swarms for explainable classifiers on data streams". Complex & Intelligent Systems, 3.04.2024. http://dx.doi.org/10.1007/s40747-024-01347-w.
Pełny tekst źródła