Addressing Fairness, Bias and Class Imbalance in Machine Learning: the
FBI-loss

Addressing Fairness, Bias and Class Imbalance in Machine Learning: the FBI-loss

13 May 2021

Papers citing "Addressing Fairness, Bias and Class Imbalance in Machine Learning: the FBI-loss"

9 / 9 papers shown

Title
Properties of fairness measures in the context of varying class imbalance and protected group ratios D. Brzezinski Julia Stachowiak Jerzy Stefanowski Izabela Szczech R. Susmaga Sofya Aksenyuk Uladzimir Ivashka Oleksandr Yasinskyi 182 5 0 13 Nov 2024
Convolutional Neural Networks based Focal Loss for Class Imbalance Problem: A Case Study of Canine Red Blood Cells Morphology Classification Kitsuchart Pasupa Supawit Vatathanavaro Suchat Tungjitnob 44 59 0 10 Jan 2020
Measuring the effects of confounders in medical supervised classification problems: the Confounding Index (CI) E. Ferrari A. Retico D. Bacciu CML 29 12 0 21 May 2019
Controllable Invariance through Adversarial Feature Learning Qizhe Xie Zihang Dai Yulun Du Eduard H. Hovy Graham Neubig OOD 76 291 0 31 May 2017
Deep Over-sampling Framework for Classifying Imbalanced Data S. Ando Chun-Yuan Huang 43 178 0 25 Apr 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations A. Ross M. C. Hughes Finale Doshi-Velez FAtt 115 585 0 10 Mar 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 850 16,828 0 16 Feb 2016
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 359 9,418 0 28 May 2015
Scalable Object Detection using Deep Neural Networks D. Erhan Christian Szegedy Alexander Toshev Dragomir Anguelov ObjD 110 1,165 0 08 Dec 2013

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