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Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

5 March 2018
Dong Yin
Yudong Chen
Kannan Ramchandran
Peter L. Bartlett
    OOD
    FedML
ArXivPDFHTML

Papers citing "Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates"

50 / 250 papers shown
Title
Poisoning Decentralized Collaborative Recommender System and Its
  Countermeasures
Poisoning Decentralized Collaborative Recommender System and Its Countermeasures
Ruiqi Zheng
Liang Qu
Tong Chen
Kai Zheng
Yuhui Shi
Hongzhi Yin
29
7
0
01 Apr 2024
Global Convergence Guarantees for Federated Policy Gradient Methods with
  Adversaries
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries
Swetha Ganesh
Jiayu Chen
Gugan Thoppe
Vaneet Aggarwal
FedML
71
1
0
15 Mar 2024
FL-GUARD: A Holistic Framework for Run-Time Detection and Recovery of
  Negative Federated Learning
FL-GUARD: A Holistic Framework for Run-Time Detection and Recovery of Negative Federated Learning
Hong Lin
Lidan Shou
Ke Chen
Gang Chen
Sai Wu
32
0
0
07 Mar 2024
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive
  Models
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
Younghan Lee
Yungi Cho
Woorim Han
Ho Bae
Y. Paek
FedML
AAML
32
2
0
05 Mar 2024
FedReview: A Review Mechanism for Rejecting Poisoned Updates in
  Federated Learning
FedReview: A Review Mechanism for Rejecting Poisoned Updates in Federated Learning
Tianhang Zheng
Baochun Li
FedML
AAML
29
0
0
26 Feb 2024
SGD with Clipping is Secretly Estimating the Median Gradient
SGD with Clipping is Secretly Estimating the Median Gradient
Fabian Schaipp
Guillaume Garrigos
Umut Simsekli
Robert M. Gower
39
0
0
20 Feb 2024
On the Byzantine-Resilience of Distillation-Based Federated Learning
On the Byzantine-Resilience of Distillation-Based Federated Learning
Christophe Roux
Max Zimmer
Sebastian Pokutta
AAML
59
1
0
19 Feb 2024
Towards Fair, Robust and Efficient Client Contribution Evaluation in
  Federated Learning
Towards Fair, Robust and Efficient Client Contribution Evaluation in Federated Learning
Meiying Zhang
Huan Zhao
Sheldon C Ebron
Kan Yang
FedML
16
2
0
06 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei
Ling Liu
31
16
0
02 Feb 2024
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated
  Learning
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning
Zhangchen Xu
Fengqing Jiang
Luyao Niu
Jinyuan Jia
Radha Poovendran
26
0
0
10 Jan 2024
Harnessing the Power of Federated Learning in Federated Contextual
  Bandits
Harnessing the Power of Federated Learning in Federated Contextual Bandits
Chengshuai Shi
Ruida Zhou
Kun Yang
Cong Shen
FedML
33
0
0
26 Dec 2023
Robustness, Efficiency, or Privacy: Pick Two in Machine Learning
Robustness, Efficiency, or Privacy: Pick Two in Machine Learning
Youssef Allouah
R. Guerraoui
John Stephan
OOD
31
2
0
22 Dec 2023
MISA: Unveiling the Vulnerabilities in Split Federated Learning
MISA: Unveiling the Vulnerabilities in Split Federated Learning
Wei Wan
Yuxuan Ning
Shengshan Hu
Lulu Xue
Minghui Li
Leo Yu Zhang
Hai Jin
14
3
0
18 Dec 2023
Layered Randomized Quantization for Communication-Efficient and
  Privacy-Preserving Distributed Learning
Layered Randomized Quantization for Communication-Efficient and Privacy-Preserving Distributed Learning
Guangfeng Yan
Tan Li
Tian-Shing Lan
Kui Wu
Linqi Song
27
6
0
12 Dec 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm
  Perspective
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective
Xianghua Xie
Chen Hu
Hanchi Ren
Jingjing Deng
FedML
AAML
53
19
0
27 Nov 2023
Backdoor Threats from Compromised Foundation Models to Federated
  Learning
Backdoor Threats from Compromised Foundation Models to Federated Learning
Xi Li
Songhe Wang
Chen Henry Wu
Hao Zhou
Jiaqi Wang
99
10
0
31 Oct 2023
Communication Compression for Byzantine Robust Learning: New Efficient
  Algorithms and Improved Rates
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates
Ahmad Rammal
Kaja Gruntkowska
Nikita Fedin
Eduard A. Gorbunov
Peter Richtárik
50
5
0
15 Oct 2023
Voyager: MTD-Based Aggregation Protocol for Mitigating Poisoning Attacks
  on DFL
Voyager: MTD-Based Aggregation Protocol for Mitigating Poisoning Attacks on DFL
Chao Feng
Alberto Huertas Celdrán
Michael Vuong
Gérome Bovet
Burkhard Stiller
AAML
24
1
0
12 Oct 2023
FLEDGE: Ledger-based Federated Learning Resilient to Inference and
  Backdoor Attacks
FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks
Jorge Castillo
Phillip Rieger
Hossein Fereidooni
Qian Chen
Ahmad Sadeghi
FedML
AAML
41
8
0
03 Oct 2023
Enabling Quartile-based Estimated-Mean Gradient Aggregation As Baseline
  for Federated Image Classifications
Enabling Quartile-based Estimated-Mean Gradient Aggregation As Baseline for Federated Image Classifications
Yusen Wu
Jamie Deng
Hao Chen
Phuong Nguyen
Yelena Yesha
FedML
34
0
0
21 Sep 2023
Byzantine-Robust Federated Learning with Variance Reduction and
  Differential Privacy
Byzantine-Robust Federated Learning with Variance Reduction and Differential Privacy
Zikai Zhang
Rui Hu
41
11
0
07 Sep 2023
Protect Federated Learning Against Backdoor Attacks via Data-Free
  Trigger Generation
Protect Federated Learning Against Backdoor Attacks via Data-Free Trigger Generation
Yanxin Yang
Ming Hu
Yue Cao
Jun Xia
Yihao Huang
Yang Liu
Mingsong Chen
FedML
31
6
0
22 Aug 2023
Communication-Efficient Search under Fully Homomorphic Encryption for
  Federated Machine Learning
Communication-Efficient Search under Fully Homomorphic Encryption for Federated Machine Learning
Dongfang Zhao
FedML
34
1
0
09 Aug 2023
FLIPS: Federated Learning using Intelligent Participant Selection
FLIPS: Federated Learning using Intelligent Participant Selection
R. Bhope
K.R. Jayaram
N. Venkatasubramanian
Ashish Verma
Gegi Thomas
FedML
36
3
0
07 Aug 2023
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning
Wei Wan
Shengshan Hu
Minghui Li
Jianrong Lu
Longling Zhang
Leo Yu Zhang
Hai Jin
AAML
FedML
42
20
0
07 Aug 2023
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks
Natalie Lang
Nir Shlezinger
Rafael G. L. DÓliveira
S. E. Rouayheb
FedML
82
4
0
01 Aug 2023
You Can Backdoor Personalized Federated Learning
You Can Backdoor Personalized Federated Learning
Tiandi Ye
Cen Chen
Yinggui Wang
Xiang Li
Ming Gao
AAML
FedML
39
4
0
29 Jul 2023
High Dimensional Distributed Gradient Descent with Arbitrary Number of
  Byzantine Attackers
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers
Puning Zhao
Zhiguo Wan
OOD
FedML
47
4
0
25 Jul 2023
FedDefender: Client-Side Attack-Tolerant Federated Learning
FedDefender: Client-Side Attack-Tolerant Federated Learning
Sungwon Park
Sungwon Han
Fangzhao Wu
Sundong Kim
Bin Zhu
Xing Xie
Meeyoung Cha
FedML
AAML
31
20
0
18 Jul 2023
A Secure Aggregation for Federated Learning on Long-Tailed Data
A Secure Aggregation for Federated Learning on Long-Tailed Data
Yanna Jiang
Baihe Ma
Xu Wang
Guangsheng Yu
Caijun Sun
W. Ni
R. Liu
FedML
29
1
0
17 Jul 2023
Byzantine-Robust Distributed Online Learning: Taming Adversarial
  Participants in An Adversarial Environment
Byzantine-Robust Distributed Online Learning: Taming Adversarial Participants in An Adversarial Environment
Xingrong Dong
Zhaoxian Wu
Qing Ling
Zhi Tian
AAML
48
9
0
16 Jul 2023
A First Order Meta Stackelberg Method for Robust Federated Learning
A First Order Meta Stackelberg Method for Robust Federated Learning
Yunian Pan
Tao Li
Henger Li
Tianyi Xu
Zizhan Zheng
Quanyan Zhu
FedML
35
10
0
23 Jun 2023
Adversarially robust clustering with optimality guarantees
Adversarially robust clustering with optimality guarantees
Soham Jana
Kun Yang
Sanjeev R. Kulkarni
AAML
34
2
0
16 Jun 2023
FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving
  Federated Learning with Byzantine Users
FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users
Y. Rahulamathavan
Charuka Herath
Xiaolan Liu
S. Lambotharan
Carsten Maple
43
12
0
08 Jun 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric
  Investigations
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations
T. Krauß
Alexandra Dmitrienko
AAML
27
4
0
06 Jun 2023
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
Florian E. Dorner
Nikola Konstantinov
Georgi Pashaliev
Martin Vechev
FedML
27
5
0
25 May 2023
On the Optimal Batch Size for Byzantine-Robust Distributed Learning
On the Optimal Batch Size for Byzantine-Robust Distributed Learning
Yi-Rui Yang
Chang-Wei Shi
Wu-Jun Li
FedML
AAML
27
0
0
23 May 2023
FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local
  Ultimate Gradients Inspection
FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection
Thuy-Dung Nguyen
Anh Duy Nguyen
Kok-Seng Wong
H. Pham
T. Nguyen
Phi Le Nguyen
Truong Thao Nguyen
FedML
AAML
36
4
0
29 Apr 2023
Attacks on Robust Distributed Learning Schemes via Sensitivity Curve
  Maximization
Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization
Christian A. Schroth
Stefan Vlaski
A. Zoubir
FedML
57
1
0
27 Apr 2023
Denial-of-Service or Fine-Grained Control: Towards Flexible Model
  Poisoning Attacks on Federated Learning
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning
Hangtao Zhang
Zeming Yao
L. Zhang
Shengshan Hu
Chao Chen
Alan Liew
Zhetao Li
32
9
0
21 Apr 2023
BadVFL: Backdoor Attacks in Vertical Federated Learning
BadVFL: Backdoor Attacks in Vertical Federated Learning
Mohammad Naseri
Yufei Han
Emiliano De Cristofaro
FedML
AAML
37
11
0
18 Apr 2023
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via
  User-configurable Privacy Defense
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense
Yue-li Cui
Syed Imran Ali Meerza
Zhuohang Li
Luyang Liu
Jiaxin Zhang
Jian-Dong Liu
AAML
FedML
34
4
0
11 Apr 2023
Online Learning with Adversaries: A Differential-Inclusion Analysis
Online Learning with Adversaries: A Differential-Inclusion Analysis
Swetha Ganesh
Alexandre Reiffers
Gugan Thoppe
FedML
45
3
0
04 Apr 2023
Secure Federated Learning against Model Poisoning Attacks via Client
  Filtering
Secure Federated Learning against Model Poisoning Attacks via Client Filtering
D. Yaldiz
Tuo Zhang
Salman Avestimehr
AAML
FedML
26
14
0
31 Mar 2023
Protecting Federated Learning from Extreme Model Poisoning Attacks via
  Multidimensional Time Series Anomaly Detection
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection
Edoardo Gabrielli
Dimitri Belli
Vittorio Miori
Gabriele Tolomei
AAML
13
4
0
29 Mar 2023
FedREP: A Byzantine-Robust, Communication-Efficient and
  Privacy-Preserving Framework for Federated Learning
FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning
Yi-Rui Yang
Kun Wang
Wulu Li
FedML
52
3
0
09 Mar 2023
Can Decentralized Learning be more robust than Federated Learning?
Can Decentralized Learning be more robust than Federated Learning?
Mathilde Raynal
Dario Pasquini
Carmela Troncoso
OOD
FedML
43
4
0
07 Mar 2023
A Survey of Trustworthy Federated Learning with Perspectives on
  Security, Robustness, and Privacy
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy
Yifei Zhang
Dun Zeng
Jinglong Luo
Zenglin Xu
Irwin King
FedML
84
48
0
21 Feb 2023
ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated
  Learning Based on Coded Computing and Vector Commitment
ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment
Tayyebeh Jahani-Nezhad
M. Maddah-ali
Giuseppe Caire
FedML
40
2
0
20 Feb 2023
BayBFed: Bayesian Backdoor Defense for Federated Learning
BayBFed: Bayesian Backdoor Defense for Federated Learning
Kavita Kumari
Phillip Rieger
Hossein Fereidooni
Murtuza Jadliwala
A. Sadeghi
AAML
FedML
31
33
0
23 Jan 2023
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