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Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance

Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance

2 February 2024
Wenqi Wei
Ling Liu
ArXivPDFHTML

Papers citing "Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance"

13 / 13 papers shown
Title
Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents
Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents
Christian Schroeder de Witt
AAML
AI4CE
150
0
0
04 May 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond
Qiongxiu Li
Xiaoyu Luo
Yiyi Chen
Johannes Bjerva
45
0
0
10 Mar 2025
Joint Universal Adversarial Perturbations with Interpretations
Joint Universal Adversarial Perturbations with Interpretations
Liang-bo Ning
Zeyu Dai
Wenqi Fan
Jingran Su
Chao Pan
Luning Wang
Qing Li
AAML
42
2
0
03 Aug 2024
Machine Learning for Synthetic Data Generation: A Review
Machine Learning for Synthetic Data Generation: A Review
Ying-Cheng Lu
Minjie Shen
Huazheng Wang
Xiao Wang
Capucine Van Rechem
Tianfan Fu
Wenqi Wei
SyDa
36
140
0
08 Feb 2023
Federated Multi-Armed Bandits
Federated Multi-Armed Bandits
Chengshuai Shi
Cong Shen
FedML
58
92
0
28 Jan 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
Xiaoyu Cao
Minghong Fang
Jia Liu
Neil Zhenqiang Gong
FedML
117
611
0
27 Dec 2020
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
290
1,815
0
14 Dec 2020
Clean-Label Backdoor Attacks on Video Recognition Models
Clean-Label Backdoor Attacks on Video Recognition Models
Shihao Zhao
Xingjun Ma
Xiang Zheng
James Bailey
Jingjing Chen
Yu-Gang Jiang
AAML
196
274
0
06 Mar 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
323
4,212
0
23 Aug 2019
Analyzing Federated Learning through an Adversarial Lens
Analyzing Federated Learning through an Adversarial Lens
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
S. Calo
FedML
182
1,032
0
29 Nov 2018
CNN-Cert: An Efficient Framework for Certifying Robustness of
  Convolutional Neural Networks
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
Akhilan Boopathy
Tsui-Wei Weng
Pin-Yu Chen
Sijia Liu
Luca Daniel
AAML
108
138
0
29 Nov 2018
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,084
0
24 Oct 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,837
0
08 Jul 2016
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