Artigos de revistas sobre o tema "Bias mitigation"
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Erkmen, Cherie Parungo, Lauren Kane e David T. Cooke. "Bias Mitigation in Cardiothoracic Recruitment". Annals of Thoracic Surgery 111, n.º 1 (janeiro de 2021): 12–15. http://dx.doi.org/10.1016/j.athoracsur.2020.07.005.
Texto completo da fonteVejsbjerg, Inge, Elizabeth M. Daly, Rahul Nair e Svetoslav Nizhnichenkov. "Interactive Human-Centric Bias Mitigation". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 21 (24 de março de 2024): 23838–40. http://dx.doi.org/10.1609/aaai.v38i21.30582.
Texto completo da fonteDjebrouni, Yasmine, Nawel Benarba, Ousmane Touat, Pasquale De Rosa, Sara Bouchenak, Angela Bonifati, Pascal Felber, Vania Marangozova e Valerio Schiavoni. "Bias Mitigation in Federated Learning for Edge Computing". Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, n.º 4 (19 de dezembro de 2023): 1–35. http://dx.doi.org/10.1145/3631455.
Texto completo da fonteGallaher, Joshua P., Alexander J. Kamrud e Brett J. Borghetti. "Detection and Mitigation of Inefficient Visual Searching". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, n.º 1 (dezembro de 2020): 47–51. http://dx.doi.org/10.1177/1071181320641015.
Texto completo da fonteRahmawati, Fitriana, e Fitri Santi. "A Literature Review on the Influence of Availability Bias and Overconfidence Bias on Investor Decisions". East Asian Journal of Multidisciplinary Research 2, n.º 12 (30 de dezembro de 2023): 4961–76. http://dx.doi.org/10.55927/eajmr.v2i12.6896.
Texto completo da fonteSingh, Richa, Puspita Majumdar, Surbhi Mittal e Mayank Vatsa. "Anatomizing Bias in Facial Analysis". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 11 (28 de junho de 2022): 12351–58. http://dx.doi.org/10.1609/aaai.v36i11.21500.
Texto completo da fonteLee, Yu-Hao, Norah E. Dunbar, Claude H. Miller, Brianna L. Lane, Matthew L. Jensen, Elena Bessarabova, Judee K. Burgoon et al. "Training Anchoring and Representativeness Bias Mitigation Through a Digital Game". Simulation & Gaming 47, n.º 6 (20 de agosto de 2016): 751–79. http://dx.doi.org/10.1177/1046878116662955.
Texto completo da fontePatil, Pranita, e Kevin Purcell. "Decorrelation-Based Deep Learning for Bias Mitigation". Future Internet 14, n.º 4 (29 de março de 2022): 110. http://dx.doi.org/10.3390/fi14040110.
Texto completo da fonteKim, Hyo-eun. "Fairness Criteria and Mitigation of AI Bias". Korean Journal of Psychology: General 40, n.º 4 (25 de dezembro de 2021): 459–85. http://dx.doi.org/10.22257/kjp.2021.12.40.4.459.
Texto completo da fontePark, Souneil, Seungwoo Kang, Sangyoung Chung e Junehwa Song. "A Computational Framework for Media Bias Mitigation". ACM Transactions on Interactive Intelligent Systems 2, n.º 2 (junho de 2012): 1–32. http://dx.doi.org/10.1145/2209310.2209311.
Texto completo da fonteHopkins, Taylor. "Bias Mitigation: Identifying Barriers and Finding Solutions". Forensic Science International: Synergy 6 (2023): 100420. http://dx.doi.org/10.1016/j.fsisyn.2023.100420.
Texto completo da fonteHudson, P., W. J. W. Botzen, H. Kreibich, P. Bubeck e J. C. J. H. Aerts. "Evaluating the effectiveness of flood damage mitigation measures by the application of propensity score matching". Natural Hazards and Earth System Sciences 14, n.º 7 (15 de julho de 2014): 1731–47. http://dx.doi.org/10.5194/nhess-14-1731-2014.
Texto completo da fonteHudson, P., W. J. W. Botzen, H. Kreibich, P. Bubeck e J. C. J. H. Aerts. "Evaluating the effectiveness of flood damage mitigation measures by the application of Propensity Score Matching". Natural Hazards and Earth System Sciences Discussions 2, n.º 1 (22 de janeiro de 2014): 681–723. http://dx.doi.org/10.5194/nhessd-2-681-2014.
Texto completo da fonteK. Devasenapathy, Arun Padmanabhan,. "Uncovering Bias: Exploring Machine Learning Techniques for Detecting and Mitigating Bias in Data – A Literature Review". International Journal on Recent and Innovation Trends in Computing and Communication 11, n.º 9 (30 de outubro de 2023): 776–81. http://dx.doi.org/10.17762/ijritcc.v11i9.8965.
Texto completo da fonteClegg, Benjamin A., Brian McKernan, Rosa M. Martey, Sarah M. Taylor, Jennifer Stromer-Galley, Kate Kenski, E. Tobi Saulnier et al. "Effective Mitigation of Anchoring Bias, Projection Bias, and Representativeness Bias from Serious Game-based Training". Procedia Manufacturing 3 (2015): 1558–65. http://dx.doi.org/10.1016/j.promfg.2015.07.438.
Texto completo da fonteCai, Zhenyu. "Quantum Error Mitigation using Symmetry Expansion". Quantum 5 (21 de setembro de 2021): 548. http://dx.doi.org/10.22331/q-2021-09-21-548.
Texto completo da fonteSiddique, Sunzida, Mohd Ariful Haque, Roy George, Kishor Datta Gupta, Debashis Gupta e Md Jobair Hossain Faruk. "Survey on Machine Learning Biases and Mitigation Techniques". Digital 4, n.º 1 (20 de dezembro de 2023): 1–68. http://dx.doi.org/10.3390/digital4010001.
Texto completo da fonteMosteiro, Pablo, Jesse Kuiper, Judith Masthoff, Floortje Scheepers e Marco Spruit. "Bias Discovery in Machine Learning Models for Mental Health". Information 13, n.º 5 (5 de maio de 2022): 237. http://dx.doi.org/10.3390/info13050237.
Texto completo da fonteDe Biasio, Francesco, e Stefano Zecchetto. "Tuning the Model Winds in Perspective of Operational Storm Surge Prediction in the Adriatic Sea". Journal of Marine Science and Engineering 11, n.º 3 (3 de março de 2023): 544. http://dx.doi.org/10.3390/jmse11030544.
Texto completo da fontePrater, James, Konstantinos Kirytopoulos e Tony Ma. "Optimism bias within the project management context". International Journal of Managing Projects in Business 10, n.º 2 (4 de abril de 2017): 370–85. http://dx.doi.org/10.1108/ijmpb-07-2016-0063.
Texto completo da fonteChu, Charlene, Simon Donato-Woodger, Shehroz Khan, Kathleen Leslie, Tianyu Shi, Rune Nyrup e Amanda Grenier. "STRATEGIES TO MITIGATE MACHINE LEARNING BIAS AFFECTING OLDER ADULTS: RESULTS FROM A SCOPING REVIEW". Innovation in Aging 7, Supplement_1 (1 de dezembro de 2023): 717–18. http://dx.doi.org/10.1093/geroni/igad104.2325.
Texto completo da fonteDunbar, Norah E., Matthew L. Jensen, Claude H. Miller, Elena Bessarabova, Yu-Hao Lee, Scott N. Wilson, Javier Elizondo et al. "Mitigation of Cognitive Bias with a Serious Game". International Journal of Game-Based Learning 7, n.º 4 (outubro de 2017): 86–100. http://dx.doi.org/10.4018/ijgbl.2017100105.
Texto completo da fonteGuan, Maime, e Joachim Vandekerckhove. "A Bayesian approach to mitigation of publication bias". Psychonomic Bulletin & Review 23, n.º 1 (1 de julho de 2015): 74–86. http://dx.doi.org/10.3758/s13423-015-0868-6.
Texto completo da fonteDavison, Robert M. "Editorial - Cultural Bias in Reviews and Mitigation Options". Information Systems Journal 24, n.º 6 (5 de agosto de 2014): 475–77. http://dx.doi.org/10.1111/isj.12046.
Texto completo da fonteKorzhenevych, I. P., e O. V. Gots. "THE MITIGATION STEERING BIAS CURVES FOR INDUSTRIAL TRANSPORT". Science and Transport Progress, n.º 16 (25 de junho de 2007): 26–28. http://dx.doi.org/10.15802/stp2007/17607.
Texto completo da fontePenn, Jerrod M., Daniel R. Petrolia e J. Matthew Fannin. "Hypothetical bias mitigation in representative and convenience samples". Applied Economic Perspectives and Policy 45, n.º 2 (18 de maio de 2023): 721–43. http://dx.doi.org/10.1002/aepp.13374.
Texto completo da fonteLi, Xuesong, Dajun Sun e Zhongyi Cao. "Mitigation method of acoustic doppler velocity measurement bias". Ocean Engineering 306 (agosto de 2024): 118082. http://dx.doi.org/10.1016/j.oceaneng.2024.118082.
Texto completo da fonteKempf, Arlo, e Preeti Nayak. "Practicing Professional Discomfort as Self-Location: White Teacher Experiences With Race Bias Mitigation". Journal of the Canadian Association for Curriculum Studies 18, n.º 1 (27 de junho de 2020): 51–52. http://dx.doi.org/10.25071/1916-4467.40584.
Texto completo da fonteKohn, Rachel. "Eliminating Bias in Survival Estimation: Statistical Bias Mitigation Is the First Step Forward*". Critical Care Medicine 52, n.º 3 (21 de fevereiro de 2024): 506–9. http://dx.doi.org/10.1097/ccm.0000000000006110.
Texto completo da fonteBulut, Solmaz, Mehdi Rostami, Shahla Shokatpour Lotfi, Naser Jafarzadeh, Sefa Bulut, Baidi Bukhori, Seyed Hadi Seyed Alitabar, Zohreh Zadhasn e Farzaneh Mardani. "The Impact of Counselor Bias in Assessment: A Comprehensive Review and Best Practices". Journal of Assessment and Research in Applied Counseling 5, n.º 4 (2023): 89–103. http://dx.doi.org/10.61838/kman.jarac.5.4.11.
Texto completo da fonteNazer, Lama H., Razan Zatarah, Shai Waldrip, Janny Xue Chen Ke, Mira Moukheiber, Ashish K. Khanna, Rachel S. Hicklen et al. "Bias in artificial intelligence algorithms and recommendations for mitigation". PLOS Digital Health 2, n.º 6 (22 de junho de 2023): e0000278. http://dx.doi.org/10.1371/journal.pdig.0000278.
Texto completo da fonteSomasundaram, Ananthi, David Vállez García, Elisabeth Pfaehler, Joyce van Sluis, Rudi A. J. O. Dierckx, Elisabeth G. E. de Vries e Ronald Boellaard. "Mitigation of noise-induced bias of PET radiomic features". PLOS ONE 17, n.º 8 (25 de agosto de 2022): e0272643. http://dx.doi.org/10.1371/journal.pone.0272643.
Texto completo da fonteBartley, Tanya, Rebecca O'Connor e Kenya Beard. "Should All Nurses Be Required to Complete Implicit Bias Training?" AJN, American Journal of Nursing 123, n.º 11 (novembro de 2023): 20–21. http://dx.doi.org/10.1097/01.naj.0000995336.31551.4e.
Texto completo da fonteSethi, Rahul, Vedang Ratan Vatsa e Parth Chhaparwal. "IDENTIFICATION AND MITIGATION OF ALGORITHMIC BIAS THROUGH POLICY INSTRUMENTS". International Journal of Advanced Research 8, n.º 7 (31 de julho de 2020): 1515–22. http://dx.doi.org/10.21474/ijar01/11418.
Texto completo da fonteAshokan, Ashwathy, e Christian Haas. "Fairness metrics and bias mitigation strategies for rating predictions". Information Processing & Management 58, n.º 5 (setembro de 2021): 102646. http://dx.doi.org/10.1016/j.ipm.2021.102646.
Texto completo da fonteFortunato, S., A. Flammini, F. Menczer e A. Vespignani. "Topical interests and the mitigation of search engine bias". Proceedings of the National Academy of Sciences 103, n.º 34 (10 de agosto de 2006): 12684–89. http://dx.doi.org/10.1073/pnas.0605525103.
Texto completo da fonteRohbani, Nezam, Mojtaba Ebrahimi, Seyed-Ghassem Miremadi e Mehdi B. Tahoori. "Bias Temperature Instability Mitigation via Adaptive Cache Size Management". IEEE Transactions on Very Large Scale Integration (VLSI) Systems 25, n.º 3 (março de 2017): 1012–22. http://dx.doi.org/10.1109/tvlsi.2016.2606579.
Texto completo da fonteLi, Roger Zhe. "Metric Optimization and Mainstream Bias Mitigation in Recommender Systems". ACM SIGIR Forum 57, n.º 2 (dezembro de 2023): 1–2. http://dx.doi.org/10.1145/3642979.3643010.
Texto completo da fonteZhang, Chunxiao. "Exploration, detection, and mitigation: Unveiling gender bias in NLP". Applied and Computational Engineering 52, n.º 1 (27 de março de 2024): 62–68. http://dx.doi.org/10.54254/2755-2721/52/20241234.
Texto completo da fonteAlshareef, Norah, Xiaohong Yuan, Kaushik Roy e Mustafa Atay. "A Study of Gender Bias in Face Presentation Attack and Its Mitigation". Future Internet 13, n.º 9 (14 de setembro de 2021): 234. http://dx.doi.org/10.3390/fi13090234.
Texto completo da fonteChu, Charlene, Simon Donato-Woodger, Shehroz S. Khan, Tianyu Shi, Kathleen Leslie, Samira Abbasgholizadeh-Rahimi, Rune Nyrup e Amanda Grenier. "Strategies to Mitigate Age-Related Bias in Machine Learning: Scoping Review". JMIR Aging 7 (22 de março de 2024): e53564. http://dx.doi.org/10.2196/53564.
Texto completo da fonteBlow, Christina Hastings, Lijun Qian, Camille Gibson, Pamela Obiomon e Xishuang Dong. "Comprehensive Validation on Reweighting Samples for Bias Mitigation via AIF360". Applied Sciences 14, n.º 9 (30 de abril de 2024): 3826. http://dx.doi.org/10.3390/app14093826.
Texto completo da fonteFeatherston, Rebecca Jean, Aron Shlonsky, Courtney Lewis, My-Linh Luong, Laura E. Downie, Adam P. Vogel, Catherine Granger, Bridget Hamilton e Karyn Galvin. "Interventions to Mitigate Bias in Social Work Decision-Making: A Systematic Review". Research on Social Work Practice 29, n.º 7 (23 de dezembro de 2018): 741–52. http://dx.doi.org/10.1177/1049731518819160.
Texto completo da fonteVega-Gonzalo, María, e Panayotis Christidis. "Fair Models for Impartial Policies: Controlling Algorithmic Bias in Transport Behavioural Modelling". Sustainability 14, n.º 14 (9 de julho de 2022): 8416. http://dx.doi.org/10.3390/su14148416.
Texto completo da fonteKurmi, Vinod K., Rishabh Sharma, Yash Vardhan Sharma e Vinay P. Namboodiri. "Gradient Based Activations for Accurate Bias-Free Learning". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 7 (28 de junho de 2022): 7255–62. http://dx.doi.org/10.1609/aaai.v36i7.20687.
Texto completo da fonteLi, Yunyi, Maria De-Arteaga e Maytal Saar-Tsechansky. "When More Data Lead Us Astray: Active Data Acquisition in the Presence of Label Bias". Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 10, n.º 1 (14 de outubro de 2022): 133–46. http://dx.doi.org/10.1609/hcomp.v10i1.21994.
Texto completo da fonteGill, Michael J., e Alexandra Pizzuto. "Unwilling to Un-Blame: Whites Who Dismiss Historical Causes of Societal Disparities Also Dismiss Personal Mitigating Information for Black Offenders". Social Cognition 40, n.º 1 (fevereiro de 2022): 55–87. http://dx.doi.org/10.1521/soco.2022.40.1.55.
Texto completo da fonteLi, Xiangchong, Yin Li e Richard Massey. "Weak gravitational lensing shear measurement with FPFS: analytical mitigation of noise bias and selection bias". Monthly Notices of the Royal Astronomical Society 511, n.º 4 (9 de fevereiro de 2022): 4850–60. http://dx.doi.org/10.1093/mnras/stac342.
Texto completo da fonteZhang, Hengrui, Wei (Wayne) Chen, James M. Rondinelli e Wei Chen. "ET-AL: Entropy-targeted active learning for bias mitigation in materials data". Applied Physics Reviews 10, n.º 2 (junho de 2023): 021403. http://dx.doi.org/10.1063/5.0138913.
Texto completo da fonteGaffney, Sean, e Vineeta Rao. "Reducing Bias in Opioid Risk Mitigation: Piloting a Pharmacy-Led Mitigation Strategy in Oncology Palliative Care". Journal of Pain and Symptom Management 67, n.º 5 (maio de 2024): e695. http://dx.doi.org/10.1016/j.jpainsymman.2024.02.165.
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