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Machine learned models exhibit bias, often because the datasets used to train them are biased.
The validity and practicality of sun-reactive skin types i through vi
Thomas B Fitzpatrick · 1988
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Facial action coding system: A technique for the measurement of facial movement
Paul Ekman, Wallace V Friesen, and John Hager · 2002
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Gaussian processes in machine learning
Carl Edward Rasmussen · 2004
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Robust real-time face detection
Paul Viola and Michael J Jones · 2004
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Eric Brochu, Vlad M Cora, and Nando De Freitas · 2010
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Unbiased look at dataset bias
Antonio Torralba and Alexei A Efros · 2011
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Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel · 2012
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Face recognition performance: Role of demographic information
Brendan F Klare, Mark J Burge, Joshua C Klontz, Richard W Vorder Bruegge, and Anil K Jain · 2012
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Practical bayesian optimization of machine learning algorithms
Jasper Snoek, Hugo Larochelle, and Ryan P Adams · 2012
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Age, gender and race estimation from unconstrained face images
Hu Han and Anil K Jain · 2014
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Labeled faces in the wild: Updates and new reporting procedures
Gary B Huang and Erik Learned-Miller · 2014
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Multi-view face detection using deep convolutional neural networks
Sachin Sudhakar Farfade, Mohammad J Saberian, and Li-Jia Li · 2015
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From facial parts responses to face detection: A deep learning approach
Shuo Yang, Ping Luo, Chen-Change Loy, and Xiaoou Tang · 2015
Cited alongside, same era.
A survey on face detection in the wild: past, present and future
Stefanos Zafeiriou, Cha Zhang, and Zhengyou Zhang · 2015
Cited alongside, same era.
Machine bias: There’s software used across the country to predict future criminals
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner · 2016
Cited alongside, same era.
Emotionet: An accurate, real-time algorithm for the automatic annotation of a million facial expressions in the wild
C Fabian Benitez-Quiroz, Ramprakash Srinivasan, and Aleix M Martinez · 2016
Cited alongside, same era.
False positives, false negatives, and false analyses: A rejoinder to machine bias: There’s software used across the country to predict future criminals. and it’s biased against blacks
Anthony W Flores, Kristin Bechtel, and Christopher T Lowenkamp · 2016
Cited alongside, same era.
Improving smiling detection with race and gender diversity
Hee Jung Ryu, Margaret Mitchell, and Hartwig Adam · 2017
Later among the works it cites.
A deeper look at dataset bias
Tatiana Tommasi, Novi Patricia, Barbara Caputo, and Tinne Tuytelaars · 2017
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Resolving the bias in electronic medical records
Kaiping Zheng, Jinyang Gao, Kee Yuan Ngiam, Beng Chin Ooi, and Wei Luen James Yip · 2017
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https://www.affectiva.com/product/emotion-sdk/ , 2018
Affdex SDK · 2018
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https://cloud.google.com/vision/ , 2018
Google Cloud Vision API · 2018
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https://www.microsoft.com/cognitive-services/en-us/faceapi , 2018
Microsoft Face API · 2018
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The perpetual line-up: Unregulated police face recognition in america
Clare Garvie · 2016
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Discovering blind spots of predictive models: Representations and policies for guided exploration
Himabindu Lakkaraju, Ece Kamar, Rich Caruana, and Eric Horvitz · 2016
Cited alongside, same era.
Affdex sdk: a cross-platform real-time multi-face expression recognition toolkit
Daniel McDuff, Abdelrahman Mahmoud, Mohammad Mavadati, May Amr, Jay Turcot, and Rana el Kaliouby · 2016
Cited alongside, same era.
Gender shades: intersectional phenotypic and demographic evaluation of face datasets and gender classifiers
Joy Adowaa Buolamwini · 2017
Cited alongside, same era.
Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan · 2017
Cited alongside, same era.
Identifying unknown unknowns in the open world: Representations and policies for guided exploration
Himabindu Lakkaraju, Ece Kamar, Rich Caruana, and Eric Horvitz · 2017
Cited alongside, same era.
Hyperface: A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition
Rajeev Ranjan, Vishal M Patel, and Rama Chellappa · 2017
Cited alongside, same era.
A coverage-based utility model for identifying unknown unknowns
Gagan Bansal and Daniel S Weld · 2018
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
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Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumeé III, and Kate Crawford · 2018
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The dataset nutrition label: A framework to drive higher data quality standards
Sarah Holland, Ahmed Hosny, Sarah Newman, Joshua Joseph, and Kasia Chmielinski · 2018
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Am-fed+: An extended dataset of naturalistic facial expressions collected in everyday settings
Daniel McDuff, May Amr, and Rana El Kaliouby · 2018
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Airsim: High-fidelity visual and physical simulation for autonomous vehicles
Shital Shah, Debadeepta Dey, Chris Lovett, and Ashish Kapoor · 2018
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