How to be Fair and Diverse?

23 October 2016

Papers citing "How to be Fair and Diverse?"

32 / 32 papers shown

Title
FAIR-FATE: Fair Federated Learning with Momentum Teresa Salazar Miguel X. Fernandes Helder Araújo Pedro Abreu FedML 84 21 0 27 Sep 2022
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 88 69 0 15 Nov 2021
Algorithm Fairness in AI for Medicine and Healthcare Richard J. Chen Tiffany Y. Chen Jana Lipkova Judy J. Wang Drew F. K. Williamson Ming Y. Lu S. Sahai Faisal Mahmood FaML 150 47 0 01 Oct 2021
A Sociotechnical View of Algorithmic Fairness Mateusz Dolata Stefan Feuerriegel Gerhard Schwabe FaML 76 101 0 27 Sep 2021
Diversity in Sociotechnical Machine Learning Systems S. Fazelpour Maria De-Arteaga 88 38 0 19 Jul 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 192 212 0 12 Jul 2021
Scalable Projection-Free Optimization Mingrui Zhang 90 0 0 07 May 2021
Socially Responsible AI Algorithms: Issues, Purposes, and Challenges Lu Cheng Kush R. Varshney Huan Liu FaML 170 153 0 01 Jan 2021
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 116 654 0 04 Oct 2020
Finding Fair and Efficient Allocations When Valuations Don't Add Up Nawal Benabbou Mithun Chakraborty Ayumi Igarashi Yair Zick 61 56 0 16 Mar 2020
Diversity and Inclusion Metrics in Subset Selection Margaret Mitchell Dylan K. Baker Nyalleng Moorosi Emily L. Denton Ben Hutchinson A. Hanna Timnit Gebru Jamie Morgenstern FaML 214 87 0 09 Feb 2020
Interventions for Ranking in the Presence of Implicit Bias L. E. Celis Anay Mehrotra Nisheeth K. Vishnoi 86 65 0 23 Jan 2020
Measuring Diversity of Artificial Intelligence Conferences Ana Freire Lorenzo Porcaro Emilia Gómez 51 28 0 20 Jan 2020
Adaptivity in Adaptive Submodularity Hossein Esfandiari Amin Karbasi Vahab Mirrokni 113 35 0 09 Nov 2019
Representation Learning with Statistical Independence to Mitigate Bias Ehsan Adeli Qingyu Zhao A. Pfefferbaum E. Sullivan Li Fei-Fei Juan Carlos Niebles K. Pohl CML FaML OOD 95 17 0 08 Oct 2019
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm Piotr Indyk S. Mahabadi S. Gharan A. Rezaei 102 21 0 06 Jul 2019
Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search S. Geyik Stuart Ambler K. Kenthapadi 115 384 0 30 Apr 2019
Implicit Diversity in Image Summarization L. E. Celis Vijay Keswani 110 35 0 29 Jan 2019
Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems Bashir Rastegarpanah Krishna P. Gummadi M. Crovella 101 119 0 02 Dec 2018
Correcting the bias in least squares regression with volume-rescaled sampling Michal Derezinski Manfred K. Warmuth Daniel J. Hsu 60 15 0 04 Oct 2018
Balanced News Using Constrained Bandit-based Personalization Sayash Kapoor Vijay Keswani Nisheeth K. Vishnoi L. E. Celis 60 4 0 24 Jun 2018
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees L. E. Celis Lingxiao Huang Vijay Keswani Nisheeth K. Vishnoi FaML 251 310 0 15 Jun 2018
Leveraged volume sampling for linear regression Michal Derezinski Manfred K. Warmuth Daniel J. Hsu 102 58 0 19 Feb 2018
Multiwinner Voting with Fairness Constraints L. E. Celis Lingxiao Huang Nisheeth K. Vishnoi 63 6 0 27 Oct 2017
Fair Personalization L. E. Celis Nisheeth K. Vishnoi FaML 59 17 0 07 Jul 2017
Semantics derived automatically from language corpora contain human-like biases Aylin Caliskan J. Bryson Arvind Narayanan 262 2,689 0 25 Aug 2016
On the Complexity of Constrained Determinantal Point Processes L. E. Celis Amit Deshpande Tarun Kathuria D. Straszak Nisheeth K. Vishnoi 106 25 0 01 Aug 2016
On Sampling and Greedy MAP Inference of Constrained Determinantal Point Processes Tarun Kathuria Amit Deshpande 75 17 0 06 Jul 2016
Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes Nima Anari S. Gharan A. Rezaei 92 130 0 16 Feb 2016
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning Alex Gittens Michael W. Mahoney 129 416 0 07 Mar 2013
Learning Mixtures of Submodular Shells with Application to Document Summarization Hui-Ching Lin J. Bilmes 125 192 0 16 Oct 2012
Determinantal point processes for machine learning Alex Kulesza B. Taskar 274 1,141 0 25 Jul 2012