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Targets in Reinforcement Learning to solve Stackelberg Security Games


Nov 30, 2022
Saptarashmi Bandyopadhyay, Chenqi Zhu, Philip Daniel, Joshua Morrison, Ethan Shay, John Dickerson

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* Appears in Proceedings of AAAI FSS-22 Symposium "Lessons Learned for Autonomous Assessment of Machine Abilities (LLAAMA)" 

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Achieving Downstream Fairness with Geometric Repair


Mar 14, 2022
Kweku Kwegyir-Aggrey, Jessica Dai, John Dickerson, Keegan Hines

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Differentiable Economics for Randomized Affine Maximizer Auctions


Feb 06, 2022
Michael Curry, Tuomas Sandholm, John Dickerson

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Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling


Oct 07, 2021
Naveen Raman, Sanket Shah, John Dickerson

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Learning Revenue-Maximizing Auctions With Differentiable Matching


Jun 15, 2021
Michael J. Curry, Uro Lyi, Tom Goldstein, John Dickerson

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Counterfactual Explanations for Machine Learning: Challenges Revisited


Jun 14, 2021
Sahil Verma, John Dickerson, Keegan Hines

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* Presented at CHI HCXAI 2021 workshop 

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Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting


Jun 14, 2021
Christine Herlihy, Aviva Prins, Aravind Srinivasan, John Dickerson

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* 27 pages, 19 figures 

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LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition


Jan 25, 2021
Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John Dickerson, Gavin Taylor, Tom Goldstein

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* Published as a conference paper at ICLR 2021 

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Counterfactual Explanations for Machine Learning: A Review


Oct 20, 2020
Sahil Verma, John Dickerson, Keegan Hines

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* 10 pages 

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