Algorithmic Factors Influencing Bias in Machine Learning

28 April 2021

Papers citing "Algorithmic Factors Influencing Bias in Machine Learning"

10 / 10 papers shown

Title
Characterising Bias in Compressed Models Sara Hooker Nyalleng Moorosi Gregory Clark Samy Bengio Emily L. Denton 67 185 0 06 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 102 640 0 04 Oct 2020
Good Counterfactuals and Where to Find Them: A Case-Based Technique for Generating Counterfactuals for Explainable AI (XAI) Mark T. Keane Barry Smyth CML 68 146 0 26 May 2020
Underestimation Bias and Underfitting in Machine Learning Padraig Cunningham Sarah Jane Delany 15 3 0 18 May 2020
What Do Compressed Deep Neural Networks Forget? Sara Hooker Aaron Courville Gregory Clark Yann N. Dauphin Andrea Frome 87 185 0 13 Nov 2019
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 215 1,580 0 20 Mar 2017
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 228 4,312 0 07 Oct 2016
Auditing Black-box Models for Indirect Influence Philip Adler Casey Falk Sorelle A. Friedler Gabriel Rybeck C. Scheidegger Brandon Smith Suresh Venkatasubramanian TDI MLAU 160 290 0 23 Feb 2016
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 201 1,986 0 11 Dec 2014
SMOTE: Synthetic Minority Over-sampling Technique Nitesh Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 371 25,646 0 09 Jun 2011