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FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis
11 references·3 citing·32 second hop
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis (2022)FairPrune: Achieving Fairness Through Pru…Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation (2020)Towards Fairness in Visual Re…Risk of Training Diagnostic Algorithms on Data with Demographic Bias (2020)Risk of Training Diagnostic A…Investigating Bias and Fairness in Facial Expression Recognition (2020)Investigating Bias and Fairne…Fairness in Deep Learning: A Computational Perspective (2020)Fairness in Deep Learning: A …Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings (2019)Turning a Blind Eye: Explicit…Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations (2019)Balanced Datasets Are Not Eno…Women Also Snowboard: Overcoming Bias in Captioning Models (2018)Women Also Snowboard: Overcom…Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Adversarial Removal of Demographic Attributes from Text Data (2018)Adversarial Removal of Demogr…Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints (2017)Men Also Like Shopping: Reduc…Data preprocessing techniques for classification without discrimination (2011)Data preprocessing techniques…Achieve fairness without demographics for dermatological disease diagnosis (2024)Achieve fairness without demo…Improving model fairness in image-based computer-aided diagnosis (2023)Improving model fairness in i…FairAdaBN: Mitigating Unfairness with Adaptive Batch Normalization and Its Application to Dermatological Disease Classification (2023)FairAdaBN: Mitigating Unfairn…Equality of Opportunity in Supervised Learning (2016)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Addressing bias in big data and AI for health care: A call for open science (2021)Semantics derived automatically from language corpora contain human-like biases (2017)Investigating Gender Bias in Language Models Using Causal Mediation Analysis (2020)Towards trustworthy LLMs: a review on debiasing and dehallucinating in large language models (2024)Discrimination in Online Ad Delivery (2013)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Fair Attribute Classification through Latent Space De-biasing (2021)Evaluation and Mitigation of Racial Bias in Clinical Machine Learning Models: Scoping Review (2022)Fairness through awareness (2012)Big Data's Disparate Impact (2014)Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science (2018)A Review on Fairness in Machine Learning (2022)Bias and Fairness in Large Language Models: A Survey (2024)Certifying and Removing Disparate Impact (2015)Artificial Intelligence Governance For Businesses (2022)AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023)Fairness in Graph Mining: A Survey (2023)Deep Facial Expression Recognition: A Survey (2020)Age Bias in Emotion Detection: An Analysis of Facial Emotion Recognition Performance on Young, Middle-Aged, and Older Adults (2021)Understanding and Mitigating Annotation Bias in Facial Expression Recognition (2021)A comprehensive survey on deep facial expression recognition: challenges, applications, and future guidelines (2023)Counterfactual Fairness (2017)Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)Towards fairer datasets (2020)Demographic Bias in Biometrics: A Survey on an Emerging Challenge (2020)Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases (2021)Trustworthy AI: A Computational Perspective (2022)
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References

  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2011Data preprocessing techniques for classification without discrimination1,304 cited
  • 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints829 cited
  • 2018Women Also Snowboard: Overcoming Bias in Captioning Models404 cited
  • 2019Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations355 cited
  • 2020Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation285 cited
  • 2018Adversarial Removal of Demographic Attributes from Text Data242 cited
  • 2019Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings225 cited
  • 2020Fairness in Deep Learning: A Computational Perspective216 cited
  • 2020Investigating Bias and Fairness in Facial Expression Recognition174 cited
  • 2020Risk of Training Diagnostic Algorithms on Data with Demographic Bias54 cited

Cited by

  • 2023Improving model fairness in image-based computer-aided diagnosis34 cited
  • 2023FairAdaBN: Mitigating Unfairness with Adaptive Batch Normalization and Its Application to Dermatological Disease Classification21 cited
  • 2024Achieve fairness without demographics for dermatological disease diagnosis

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14 cited