Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks
with Knowledge Distillation

Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation

15 June 2021

Nathaniel Huish

Yan Yan

Papers citing "Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation"

7 / 7 papers shown

Title
Beyond Accuracy: A Critical Review of Fairness in Machine Learning for Mobile and Wearable Computing Sofia Yfantidou Marios Constantinides Dimitris Spathis Athena Vakali Daniele Quercia F. Kawsar HAI FaML 28 18 0 27 Mar 2023
Debiased Distillation by Transplanting the Last Layer Jiwoon Lee Jaeho Lee 23 3 0 22 Feb 2023
FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute Classification Xiao-Ze Lin Seungbae Kim Jungseock Joo CVBM 37 38 0 22 Jul 2022
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm Aidan Good Jia-Huei Lin Hannah Sieg Mikey Ferguson Xin Yu Shandian Zhe J. Wieczorek Thiago Serra 37 11 0 07 Jun 2022
Pruning has a disparate impact on model accuracy Cuong Tran Ferdinando Fioretto Jung-Eun Kim Rakshit Naidu 41 38 0 26 May 2022
Data-Efficient Pretraining via Contrastive Self-Supervision Nils Rethmeier Isabelle Augenstein 23 20 0 02 Oct 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 335 4,223 0 23 Aug 2019