Politics of Adversarial Machine Learning

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Politics of Adversarial Machine Learning

1 February 2020

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Papers citing "Politics of Adversarial Machine Learning"

13 / 13 papers shown

Title
Online Algorithmic Recourse by Collective Action Elliot Creager Richard Zemel 42 4 0 29 Dec 2023
Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally Shawqi Al-Maliki Adnan Qayyum Hassan Ali M. Abdallah Junaid Qadir D. Hoang Dusit Niyato Ala I. Al-Fuqaha AAML 121 3 0 05 Oct 2023
FACE-AUDITOR: Data Auditing in Facial Recognition Systems Min Chen Zhikun Zhang Tianhao Wang Michael Backes Yang Zhang CVBM 90 17 0 05 Apr 2023
Algorithmic Collective Action in Machine Learning Moritz Hardt Eric Mazumdar Celestine Mendler-Dünner Tijana Zrnic 72 22 0 08 Feb 2023
Adversarial Robustness for Tabular Data through Cost and Utility Awareness Klim Kireev B. Kulynych Carmela Troncoso AAML 91 18 0 27 Aug 2022
Catastrophic overfitting can be induced with discriminative non-robust features Guillermo Ortiz-Jiménez Pau de Jorge Amartya Sanyal Adel Bibi P. Dokania P. Frossard Grégory Rogez Philip Torr AAML 61 3 0 16 Jun 2022
Identifying Adversarial Attacks on Text Classifiers Zhouhang Xie Jonathan Brophy Adam Noack Wencong You Kalyani Asthana Carter Perkins Sabrina Reis Sameer Singh Daniel Lowd AAML 84 10 0 21 Jan 2022
Addressing Privacy Threats from Machine Learning Mary Anne Smart 59 2 0 25 Oct 2021
The Role of Social Movements, Coalitions, and Workers in Resisting Harmful Artificial Intelligence and Contributing to the Development of Responsible AI Susan von Struensee 20 3 0 11 Jul 2021
Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks Kendra Albert Maggie K. Delano B. Kulynych Ramnath Kumar AAML 133 5 0 11 Jul 2021
FoggySight: A Scheme for Facial Lookup Privacy Ivan Evtimov Pascal Sturmfels Tadayoshi Kohno PICV FedML 76 24 0 15 Dec 2020
Pitfalls in Machine Learning Research: Reexamining the Development Cycle Stella Biderman Walter J. Scheirer 79 26 0 04 Nov 2020
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift Zayd Hammoudeh Daniel Lowd 80 39 0 24 Feb 2020