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Federated Adversarial Training with Transformers

Federated Adversarial Training with Transformers

5 June 2022
Ahmed Aldahdooh
W. Hamidouche
Olivier Déforges
    FedML
    ViT
ArXivPDFHTML

Papers citing "Federated Adversarial Training with Transformers"

16 / 16 papers shown
Title
Federated Learning Meets Natural Language Processing: A Survey
Federated Learning Meets Natural Language Processing: A Survey
Ming Liu
Stella Ho
Mengqi Wang
Longxiang Gao
Yuan Jin
Heng Zhang
FedML
32
67
0
27 Jul 2021
Federated Learning on Non-IID Data: A Survey
Federated Learning on Non-IID Data: A Survey
Hangyu Zhu
Jinjin Xu
Shiqing Liu
Yaochu Jin
OOD
FedML
60
785
0
12 Jun 2021
Rethinking Architecture Design for Tackling Data Heterogeneity in
  Federated Learning
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning
Liangqiong Qu
Yuyin Zhou
Paul Pu Liang
Yingda Xia
Feifei Wang
Ehsan Adeli
L. Fei-Fei
D. Rubin
FedML
AI4CE
30
178
0
10 Jun 2021
Adversarial Example Detection for DNN Models: A Review and Experimental
  Comparison
Adversarial Example Detection for DNN Models: A Review and Experimental Comparison
Ahmed Aldahdooh
W. Hamidouche
Sid Ahmed Fezza
Olivier Déforges
AAML
111
122
0
01 May 2021
Adversarial Attacks are Reversible with Natural Supervision
Adversarial Attacks are Reversible with Natural Supervision
Chengzhi Mao
Mia Chiquer
Hao Wang
Junfeng Yang
Carl Vondrick
BDL
AAML
55
56
0
26 Mar 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
289
855
0
01 Mar 2021
Pre-Trained Image Processing Transformer
Pre-Trained Image Processing Transformer
Hanting Chen
Yunhe Wang
Tianyu Guo
Chang Xu
Yiping Deng
Zhenhua Liu
Siwei Ma
Chunjing Xu
Chao Xu
Wen Gao
VLM
ViT
123
1,659
0
01 Dec 2020
Data Poisoning Attacks Against Federated Learning Systems
Data Poisoning Attacks Against Federated Learning Systems
Vale Tolpegin
Stacey Truex
Mehmet Emre Gursoy
Ling Liu
FedML
103
648
0
16 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated
  Optimization
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
Jianyu Wang
Qinghua Liu
Hao Liang
Gauri Joshi
H. Vincent Poor
MoMe
FedML
45
1,321
0
15 Jul 2020
Federated Learning with Compression: Unified Analysis and Sharp
  Guarantees
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour
Mohammad Mahdi Kamani
Aryan Mokhtari
M. Mahdavi
FedML
61
275
0
02 Jul 2020
Federated Learning for 6G Communications: Challenges, Methods, and
  Future Directions
Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
Yi Liu
Lizhen Qu
Zehui Xiong
Jiawen Kang
Xiaofei Wang
Dusit Niyato
FedML
AI4CE
40
280
0
04 Jun 2020
Agnostic Federated Learning
Agnostic Federated Learning
M. Mohri
Gary Sivek
A. Suresh
FedML
90
928
0
01 Feb 2019
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
Chen Sun
Abhinav Shrivastava
Saurabh Singh
Abhinav Gupta
VLM
110
2,386
0
10 Jul 2017
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
450
3,124
0
04 Nov 2016
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly
  Convex Composite Objectives
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
Aaron Defazio
Francis R. Bach
Simon Lacoste-Julien
ODL
110
1,817
0
01 Jul 2014
Minimizing Finite Sums with the Stochastic Average Gradient
Minimizing Finite Sums with the Stochastic Average Gradient
Mark Schmidt
Nicolas Le Roux
Francis R. Bach
253
1,246
0
10 Sep 2013
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