SoK: Machine Learning Governance

20 September 2021

Papers citing "SoK: Machine Learning Governance"

25 / 25 papers shown

Title
Towards Data Governance of Frontier AI Models Jason Hausenloy Duncan McClements Madhavendra Thakur 72 1 0 05 Dec 2024
SoK: Decentralized AI (DeAI) Zhipeng Wang Rui Sun Elizabeth Lui Vatsal Shah Xihan Xiong Jiahao Sun Davide Crapis William Knottenbelt 96 1 0 26 Nov 2024
SoK: Dataset Copyright Auditing in Machine Learning Systems L. Du Xuanru Zhou M. Chen Chusong Zhang Zhou Su Peng Cheng Jiming Chen Zhikun Zhang MLAU 21 3 0 22 Oct 2024
A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed Identity of DNN Model Tianxiu Xie Keke Gai Jing Yu Liehuang Zhu Kim-Kwang Raymond Choo 27 0 0 07 May 2024
ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks Eleanor Clifford Ilia Shumailov Yiren Zhao Ross J. Anderson Robert D. Mullins 23 12 0 30 Sep 2022
Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations Zirui Peng Shaofeng Li Guoxing Chen Cheng Zhang Haojin Zhu Minhui Xue AAML FedML 31 66 0 17 Feb 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 194 345 0 15 Dec 2021
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning Anvith Thudi Hengrui Jia Ilia Shumailov Nicolas Papernot MU 8 141 0 22 Oct 2021
Mitigating Dataset Harms Requires Stewardship: Lessons from 1000 Papers Kenny Peng Arunesh Mathur Arvind Narayanan 99 93 0 06 Aug 2021
Deduplicating Training Data Makes Language Models Better Katherine Lee Daphne Ippolito A. Nystrom Chiyuan Zhang Douglas Eck Chris Callison-Burch Nicholas Carlini SyDa 242 592 0 14 Jul 2021
Poisoning the Unlabeled Dataset of Semi-Supervised Learning Nicholas Carlini AAML 149 68 0 04 May 2021
Dataset Inference: Ownership Resolution in Machine Learning Pratyush Maini Mohammad Yaghini Nicolas Papernot FedML 69 104 0 21 Apr 2021
Manipulating SGD with Data Ordering Attacks Ilia Shumailov Zakhar Shumaylov Dmitry Kazhdan Yiren Zhao Nicolas Papernot Murat A. Erdogdu Ross J. Anderson AAML 112 90 0 19 Apr 2021
Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems Yue Gao Ilia Shumailov Kassem Fawaz AAML 27 10 0 18 Apr 2021
Practical and Private (Deep) Learning without Sampling or Shuffling Peter Kairouz Brendan McMahan Shuang Song Om Thakkar Abhradeep Thakurta Zheng Xu FedML 182 154 0 26 Feb 2021
CaPC Learning: Confidential and Private Collaborative Learning Christopher A. Choquette-Choo Natalie Dullerud Adam Dziedzic Yunxiang Zhang S. Jha Nicolas Papernot Xiao Wang FedML 65 57 0 09 Feb 2021
Cryptanalytic Extraction of Neural Network Models Nicholas Carlini Matthew Jagielski Ilya Mironov FedML MLAU MIACV AAML 70 134 0 10 Mar 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 107 130 0 07 Feb 2020
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 122 297 0 17 Oct 2019
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 742 0 13 Dec 2018
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 279 10,354 0 12 Dec 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 114 395 0 08 Jun 2018
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 245 914 0 21 Apr 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,660 0 05 Dec 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,835 0 08 Jul 2016