Ian Davidson

Scalable Spectral Clustering with Group Fairness Constraints

Oct 28, 2022
Ji Wang, Ding Lu, Zhaojun Bai, Ian Davidson

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Towards Auditing Unsupervised Learning Algorithms and Human Processes For Fairness

Sep 20, 2022
Ian Davidson, S. S. Ravi

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* 22 pages, 3 figures

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Explainable Clustering via Exemplars: Complexity and Efficient Approximation Algorithms

Sep 20, 2022
Ian Davidson, Michael Livanos, Antoine Gourru, Peter Walker, Julien Velcin, S. S. Ravi

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* 22 pages; 4 figures

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Deep Fair Discriminative Clustering

May 28, 2021
Hongjing Zhang, Ian Davidson

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Deep Descriptive Clustering

May 24, 2021
Hongjing Zhang, Ian Davidson

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* Paper accepted at IJCAI 2021

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A Framework for Deep Constrained Clustering

Jan 07, 2021
Hongjing Zhang, Tianyang Zhan, Sugato Basu, Ian Davidson

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* Data Mining and Knowledge Discovery, 2021. arXiv admin note: substantial text overlap with arXiv:1901.10061

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Towards Fair Deep Anomaly Detection

Dec 29, 2020
Hongjing Zhang, Ian Davidson

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* Accepted for publication at the ACM Conference on Fairness, Accountability, and Transparency 2021 (ACM FAccT'21)

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Block Model Guided Unsupervised Feature Selection

Jul 05, 2020
Zilong Bai, Hoa Nguyen, Ian Davidson

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* Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2020)
* Published at KDD2020

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Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability

Feb 06, 2020
Prathyush Sambaturu, Aparna Gupta, Ian Davidson, S. S. Ravi, Anil Vullikanti, Andrew Warren

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A Graph-Based Approach for Active Learning in Regression

Jan 30, 2020
Hongjing Zhang, S. S. Ravi, Ian Davidson

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* SDM 2020 camera-ready. 9 pages, 4 figures, links to supplementary material available at https://sdm2020.s3-us-west-1.amazonaws.com/supplementary.pdf

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