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Suresh Venkatasubramanian

Interdisciplinary Approaches to Understanding Artificial Intelligence's Impact on Society


Dec 11, 2020
Suresh Venkatasubramanian, Nadya Bliss, Helen Nissenbaum, Melanie Moses

* A Computing Community Consortium (CCC) white paper, 5 pages 

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Fair clustering via equitable group representations


Jun 19, 2020
Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian

* 15 pages, 4 figures 

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Problems with Shapley-value-based explanations as feature importance measures


Feb 25, 2020
I. Elizabeth Kumar, Suresh Venkatasubramanian, Carlos Scheidegger, Sorelle Friedler


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Equalizing Recourse across Groups


Sep 07, 2019
Vivek Gupta, Pegah Nokhiz, Chitradeep Dutta Roy, Suresh Venkatasubramanian

* 13 pages, 4 figures, 2 tables 

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Disentangling Influence: Using Disentangled Representations to Audit Model Predictions


Jun 20, 2019
Charles T. Marx, Richard Lanas Phillips, Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian


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Fairness in representation: quantifying stereotyping as a representational harm


Jan 28, 2019
Mohsen Abbasi, Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian

* 9 pages, 6 figures, Siam International Conference on Data Mining 

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A comparative study of fairness-enhancing interventions in machine learning


Feb 13, 2018
Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, Sonam Choudhary, Evan P. Hamilton, Derek Roth


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Runaway Feedback Loops in Predictive Policing


Dec 22, 2017
Danielle Ensign, Sorelle A. Friedler, Scott Neville, Carlos Scheidegger, Suresh Venkatasubramanian

* Extended version accepted to the 1st Conference on Fairness, Accountability and Transparency, 2018. Adds further treatment of reported as well as discovered incidents 

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Fair Pipelines


Jul 03, 2017
Amanda Bower, Sarah N. Kitchen, Laura Niss, Martin J. Strauss, Alexander Vargas, Suresh Venkatasubramanian

* Presented as a poster at the 2017 Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2017) 

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Auditing Black-box Models for Indirect Influence


Nov 30, 2016
Philip Adler, Casey Falk, Sorelle A. Friedler, Gabriel Rybeck, Carlos Scheidegger, Brandon Smith, Suresh Venkatasubramanian

* Final version of paper that appears in the IEEE International Conference on Data Mining (ICDM), 2016 

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On the (im)possibility of fairness


Sep 23, 2016
Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian


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A Unified View of Localized Kernel Learning


Mar 04, 2016
John Moeller, Sarathkrishna Swaminathan, Suresh Venkatasubramanian

* 14 pages, 2 figures, 4 tables. Reformatted version of the accepted SDM 2016 paper 

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Certifying and removing disparate impact


Jul 16, 2015
Michael Feldman, Sorelle Friedler, John Moeller, Carlos Scheidegger, Suresh Venkatasubramanian

* Extended version of paper accepted at 2015 ACM SIGKDD Conference on Knowledge Discovery and Data Mining 

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A Group Theoretic Perspective on Unsupervised Deep Learning


Apr 21, 2015
Arnab Paul, Suresh Venkatasubramanian

* 2-page version of arXiv:1412.6621 prepared for presentation at ICLR 2015 workshop as required by ICLR PC). This version has some minor formatting changes as required by the conference 

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Why does Deep Learning work? - A perspective from Group Theory


Feb 28, 2015
Arnab Paul, Suresh Venkatasubramanian

* 13 pages, 5 figures 

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A Geometric Algorithm for Scalable Multiple Kernel Learning


Mar 15, 2014
John Moeller, Parasaran Raman, Avishek Saha, Suresh Venkatasubramanian

* 20 pages 

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Power to the Points: Validating Data Memberships in Clusterings


May 21, 2013
Parasaran Raman, Suresh Venkatasubramanian

* 18 pages, 9 figures, 5 tables 

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Efficient Protocols for Distributed Classification and Optimization


Apr 16, 2012
Hal Daume III, Jeff M. Phillips, Avishek Saha, Suresh Venkatasubramanian


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Protocols for Learning Classifiers on Distributed Data


Feb 27, 2012
Hal Daume III, Jeff M. Phillips, Avishek Saha, Suresh Venkatasubramanian

* 19 pages, 12 figures, accepted at AISTATS 2012 

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Generating a Diverse Set of High-Quality Clusterings


Jul 29, 2011
Jeff M. Phillips, Parasaran Raman, Suresh Venkatasubramanian

* 12 Pages, 5 Figures, 2nd MultiClust Workshop at ECML PKDD 2011 

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Comparing Distributions and Shapes using the Kernel Distance


Mar 13, 2011
Sarang Joshi, Raj Varma Kommaraju, Jeff M. Phillips, Suresh Venkatasubramanian

* 20 pages. In Proceedings 27th Symposium on Computational Geometry, 2011. See also (http://arxiv.org/abs/1103.1625) for more background on the kernel distance 

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A Gentle Introduction to the Kernel Distance


Mar 09, 2011
Jeff M. Phillips, Suresh Venkatasubramanian


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Spatially-Aware Comparison and Consensus for Clusterings


Jan 31, 2011
Parasaran Raman, Jeff M. Phillips, Suresh Venkatasubramanian

* 12 Pages, 9 figures, Proceedings of 2011 Siam International Conference on Data Mining 

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A Unified Algorithmic Framework for Multi-Dimensional Scaling


Mar 30, 2010
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasubramanian

* 18 pages, 7 figures. This version fixes a bug in the proof of Theorem 6.1 (dimensionality reduction for spherical data). The statement of the result remains the same. 

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Streamed Learning: One-Pass SVMs


Aug 05, 2009
Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian

* IJCAI 2009 

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