Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks

8 October 2021

Yan Yan

Papers citing "Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks"

25 / 25 papers shown

Title
Rethinking Spatial Dimensions of Vision Transformers Byeongho Heo Sangdoo Yun Dongyoon Han Sanghyuk Chun Junsuk Choe Seong Joon Oh ViT 517 582 0 30 Mar 2021
Training data-efficient image transformers & distillation through attention Hugo Touvron Matthieu Cord Matthijs Douze Francisco Massa Alexandre Sablayrolles Hervé Jégou ViT 389 6,805 0 23 Dec 2020
Characterising Bias in Compressed Models Sara Hooker Nyalleng Moorosi Gregory Clark Samy Bengio Emily L. Denton 70 185 0 06 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 102 646 0 04 Oct 2020
Towards a Measure of Individual Fairness for Deep Learning Krystal Maughan Joseph P. Near TDI FaML 49 5 0 28 Sep 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 889 42,463 0 28 May 2020
Knapsack Pruning with Inner Distillation Y. Aflalo Asaf Noy Ming Lin Itamar Friedman Lihi Zelnik-Manor 3DPC 55 34 0 19 Feb 2020
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation Zeyu Wang Klint Qinami Yannis Karakozis Kyle Genova P. Nair Kenji Hata Olga Russakovsky 83 364 0 26 Nov 2019
What Do Compressed Deep Neural Networks Forget? Sara Hooker Aaron Courville Gregory Clark Yann N. Dauphin Andrea Frome 89 185 0 13 Nov 2019
Contrastive Representation Distillation Yonglong Tian Dilip Krishnan Phillip Isola 168 1,054 0 23 Oct 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 571 4,391 0 23 Aug 2019
Similarity-Preserving Knowledge Distillation Frederick Tung Greg Mori 126 981 0 23 Jul 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 167 18,193 0 28 May 2019
Searching for MobileNetV3 Andrew G. Howard Mark Sandler Grace Chu Liang-Chieh Chen Bo Chen ... Yukun Zhu Ruoming Pang Vijay Vasudevan Quoc V. Le Hartwig Adam 370 6,811 0 06 May 2019
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification Daniel Borkan Lucas Dixon Jeffrey Scott Sorensen Nithum Thain Lucy Vasserman 90 493 0 11 Mar 2019
Model Cards for Model Reporting Margaret Mitchell Simone Wu Andrew Zaldivar Parker Barnes Lucy Vasserman Ben Hutchinson Elena Spitzer Inioluwa Deborah Raji Timnit Gebru 137 1,908 0 05 Oct 2018
Evaluating Fairness Metrics in the Presence of Dataset Bias J. Hinnefeld Peter Cooman Nat Mammo Rupert Deese FaML 41 36 0 24 Sep 2018
Learning Deep Representations with Probabilistic Knowledge Transfer Nikolaos Passalis Anastasios Tefas 63 412 0 28 Mar 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks Mark Sandler Andrew G. Howard Menglong Zhu A. Zhmoginov Liang-Chieh Chen 209 19,335 0 13 Jan 2018
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 197 1,282 0 05 Oct 2017
Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer Sergey Zagoruyko N. Komodakis 147 2,586 0 12 Dec 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,510 0 10 Dec 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 367 19,745 0 09 Mar 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 247 8,429 0 28 Nov 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,615 0 01 Sep 2014