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Towards Fair Deep Clustering With Multi-State Protected Variables

Towards Fair Deep Clustering With Multi-State Protected Variables

29 January 2019
Bokun Wang
Ian Davidson
    FaML
    FedML
ArXivPDFHTML

Papers citing "Towards Fair Deep Clustering With Multi-State Protected Variables"

8 / 8 papers shown
Title
From Discrete to Continuous: Deep Fair Clustering With Transferable
  Representations
From Discrete to Continuous: Deep Fair Clustering With Transferable Representations
Xiang Zhang
32
0
0
24 Mar 2024
Robust Fair Clustering: A Novel Fairness Attack and Defense Framework
Robust Fair Clustering: A Novel Fairness Attack and Defense Framework
Anshuman Chhabra
Peizhao Li
P. Mohapatra
Hongfu Liu
OOD
23
22
0
04 Oct 2022
Deep Fair Clustering via Maximizing and Minimizing Mutual Information:
  Theory, Algorithm and Metric
Deep Fair Clustering via Maximizing and Minimizing Mutual Information: Theory, Algorithm and Metric
Pengxin Zeng
Yunfan Li
Peng Hu
Dezhong Peng
Jiancheng Lv
Xiaocui Peng
20
12
0
26 Sep 2022
Efficient Algorithms For Fair Clustering with a New Fairness Notion
Efficient Algorithms For Fair Clustering with a New Fairness Notion
Shivam Gupta
Ganesh Ghalme
N. C. Krishnan
Shweta Jain
FaML
60
8
0
02 Sep 2021
FiSH: Fair Spatial Hotspots
FiSH: Fair Spatial Hotspots
Deepak P
Sowmya S. Sundaram
29
1
0
01 Jun 2021
Fair clustering via equitable group representations
Fair clustering via equitable group representations
Mohsen Abbasi
Aditya Bhaskara
Suresh Venkatasubramanian
FaML
FedML
31
86
0
19 Jun 2020
Fair Outlier Detection
Fair Outlier Detection
D. P.
Savitha Sam Abraham
FaML
28
18
0
20 May 2020
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
233
674
0
17 Feb 2018
1