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LEAF: A Benchmark for Federated Settings

LEAF: A Benchmark for Federated Settings

3 December 2018
S. Caldas
Sai Meher Karthik Duddu
Peter Wu
Tian Li
Jakub Konecný
H. B. McMahan
Virginia Smith
Ameet Talwalkar
    FedML
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Papers citing "LEAF: A Benchmark for Federated Settings"

50 / 291 papers shown
Title
Federated learning: Applications, challenges and future directions
Federated learning: Applications, challenges and future directions
Subrato Bharati
Hossain Mondal
Prajoy Podder
V. B. Surya Prasath
FedML
39
53
0
18 May 2022
Label-Efficient Self-Supervised Federated Learning for Tackling Data
  Heterogeneity in Medical Imaging
Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging
Rui Yan
Liangqiong Qu
Qingyue Wei
Shih-Cheng Huang
Liyue Shen
D. Rubin
Lei Xing
Yuyin Zhou
FedML
78
90
0
17 May 2022
Decentral and Incentivized Federated Learning Frameworks: A Systematic
  Literature Review
Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review
Leon Witt
Mathis Heyer
Kentaroh Toyoda
Wojciech Samek
Dan Li
FedML
33
47
0
07 May 2022
A review of Federated Learning in Intrusion Detection Systems for IoT
A review of Federated Learning in Intrusion Detection Systems for IoT
Aitor Belenguer
J. Navaridas
J. A. Pascual
25
15
0
26 Apr 2022
A Closer Look at Personalization in Federated Image Classification
A Closer Look at Personalization in Federated Image Classification
Changxing Jing
Yan Huang
Yihong Zhuang
Liyan Sun
Yue Huang
Zhenlong Xiao
Xinghao Ding
35
1
0
22 Apr 2022
FedVQCS: Federated Learning via Vector Quantized Compressed Sensing
FedVQCS: Federated Learning via Vector Quantized Compressed Sensing
Yong-Nam Oh
Yo-Seb Jeon
Mingzhe Chen
Walid Saad
FedML
22
10
0
16 Apr 2022
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient
  Package for Federated Graph Learning
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
Zhen Wang
Weirui Kuang
Yuexiang Xie
Liuyi Yao
Yaliang Li
Bolin Ding
Jingren Zhou
FedML
13
77
0
12 Apr 2022
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
Yuexiang Xie
Zhen Wang
Dawei Gao
Daoyuan Chen
Liuyi Yao
Weirui Kuang
Yaliang Li
Bolin Ding
Jingren Zhou
FedML
21
88
0
11 Apr 2022
Divergence-aware Federated Self-Supervised Learning
Divergence-aware Federated Self-Supervised Learning
Weiming Zhuang
Yonggang Wen
Shuai Zhang
FedML
22
97
0
09 Apr 2022
FedSynth: Gradient Compression via Synthetic Data in Federated Learning
FedSynth: Gradient Compression via Synthetic Data in Federated Learning
Shengyuan Hu
Jack Goetz
Kshitiz Malik
Hongyuan Zhan
Zhe Liu
Yue Liu
DD
FedML
37
38
0
04 Apr 2022
ScaleSFL: A Sharding Solution for Blockchain-Based Federated Learning
ScaleSFL: A Sharding Solution for Blockchain-Based Federated Learning
Evan W. R. Madill
Ben Nguyen
C. Leung
Sara Rouhani
30
20
0
04 Apr 2022
Federated Learning Framework Coping with Hierarchical Heterogeneity in
  Cooperative ITS
Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS
Rui Song
Liguo Zhou
Venkatnarayanan Lakshminarasimhan
Andreas Festag
Alois C. Knoll
14
23
0
01 Apr 2022
Adaptive Aggregation For Federated Learning
Adaptive Aggregation For Federated Learning
K. R. Jayaram
Vinod Muthusamy
Gegi Thomas
Ashish Verma
Mark Purcell
FedML
27
16
0
23 Mar 2022
Training a Tokenizer for Free with Private Federated Learning
Training a Tokenizer for Free with Private Federated Learning
Eugene Bagdasaryan
Congzheng Song
Rogier van Dalen
M. Seigel
Áine Cahill
FedML
22
5
0
15 Mar 2022
Towards a Roadmap on Software Engineering for Responsible AI
Towards a Roadmap on Software Engineering for Responsible AI
Qinghua Lu
Liming Zhu
Xiwei Xu
Jon Whittle
Zhenchang Xing
28
53
0
09 Mar 2022
Towards Tailored Models on Private AIoT Devices: Federated Direct Neural
  Architecture Search
Towards Tailored Models on Private AIoT Devices: Federated Direct Neural Architecture Search
Chunhui Zhang
Xiaoming Yuan
Qianyun Zhang
Guangxu Zhu
Lei Cheng
Ning Zhang
FedML
OOD
13
15
0
23 Feb 2022
FedCAT: Towards Accurate Federated Learning via Device Concatenation
FedCAT: Towards Accurate Federated Learning via Device Concatenation
Ming Hu
Tian Liu
Zhiwei Ling
Zhihao Yue
Mingsong Chen
FedML
18
1
0
23 Feb 2022
PerFED-GAN: Personalized Federated Learning via Generative Adversarial
  Networks
PerFED-GAN: Personalized Federated Learning via Generative Adversarial Networks
Xingjian Cao
Gang Sun
Hongfang Yu
Mohsen Guizani
FedML
18
56
0
18 Feb 2022
Architecture Agnostic Federated Learning for Neural Networks
Architecture Agnostic Federated Learning for Neural Networks
Disha Makhija
Xing Han
Nhat Ho
Joydeep Ghosh
FedML
21
40
0
15 Feb 2022
Comparative assessment of federated and centralized machine learning
Comparative assessment of federated and centralized machine learning
Ibrahim Abdul Majeed
Sagar Kaushik
Aniruddha Bardhan
Venkata Siva Kumar Tadi
Hwang-Ki Min
K. Kumaraguru
Rajasekhara Reddy Duvvuru Muni
FedML
20
6
0
03 Feb 2022
Fast Server Learning Rate Tuning for Coded Federated Dropout
Fast Server Learning Rate Tuning for Coded Federated Dropout
Giacomo Verardo
Daniela F. Barreira
Marco Chiesa
Dejan Kostić
Gerald Q. Maguire Jr
FedML
27
1
0
26 Jan 2022
Communication-Efficient Device Scheduling for Federated Learning Using
  Stochastic Optimization
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization
Jake B. Perazzone
Shiqiang Wang
Mingyue Ji
Kevin S. Chan
FedML
21
72
0
19 Jan 2022
FedDTG:Federated Data-Free Knowledge Distillation via Three-Player
  Generative Adversarial Networks
FedDTG:Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks
Zhenyuan Zhang
Tao Shen
Jie M. Zhang
Chao-Xiang Wu
FedML
15
13
0
10 Jan 2022
FedBalancer: Data and Pace Control for Efficient Federated Learning on
  Heterogeneous Clients
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients
Jaemin Shin
Yuanchun Li
Yunxin Liu
Sung-Ju Lee
FedML
17
73
0
05 Jan 2022
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Boxin Zhao
Lingxiao Wang
Mladen Kolar
Ziqi Liu
Qing Cui
Jun Zhou
Chaochao Chen
FedML
34
10
0
28 Dec 2021
DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems
DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems
Martin Rapp
R. Khalili
Kilian Pfeiffer
J. Henkel
19
18
0
16 Dec 2021
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with
  Sparsification
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
Ashwinee Panda
Saeed Mahloujifar
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
FedML
AAML
9
84
0
12 Dec 2021
Efficient Federated Learning for AIoT Applications Using Knowledge
  Distillation
Efficient Federated Learning for AIoT Applications Using Knowledge Distillation
Tian Liu
Xian Wei
Jun Xia
Xin Fu
Ting Wang
Mingsong Chen
6
15
0
29 Nov 2021
Personalized Federated Learning through Local Memorization
Personalized Federated Learning through Local Memorization
Othmane Marfoq
Giovanni Neglia
Laetitia Kameni
Richard Vidal
FedML
27
87
0
17 Nov 2021
Papaya: Practical, Private, and Scalable Federated Learning
Papaya: Practical, Private, and Scalable Federated Learning
Dzmitry Huba
John Nguyen
Kshitiz Malik
Ruiyu Zhu
Michael G. Rabbat
...
H. Srinivas
Kaikai Wang
Anthony Shoumikhin
Jesik Min
Mani Malek
FedML
110
137
0
08 Nov 2021
FedLess: Secure and Scalable Federated Learning Using Serverless
  Computing
FedLess: Secure and Scalable Federated Learning Using Serverless Computing
Andreas Grafberger
Mohak Chadha
Anshul Jindal
Jianfeng Gu
Michael Gerndt
36
49
0
05 Nov 2021
Resource-Efficient Federated Learning
Resource-Efficient Federated Learning
A. Abdelmoniem
Atal Narayan Sahu
Marco Canini
Suhaib A. Fahmy
FedML
32
52
0
01 Nov 2021
DAdaQuant: Doubly-adaptive quantization for communication-efficient
  Federated Learning
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning
Robert Hönig
Yiren Zhao
Robert D. Mullins
FedML
109
54
0
31 Oct 2021
What Do We Mean by Generalization in Federated Learning?
What Do We Mean by Generalization in Federated Learning?
Honglin Yuan
Warren Morningstar
Lin Ning
K. Singhal
OOD
FedML
41
71
0
27 Oct 2021
TESSERACT: Gradient Flip Score to Secure Federated Learning Against
  Model Poisoning Attacks
TESSERACT: Gradient Flip Score to Secure Federated Learning Against Model Poisoning Attacks
Atul Sharma
Wei Chen
Joshua C. Zhao
Qiang Qiu
Somali Chaterji
S. Bagchi
FedML
AAML
46
5
0
19 Oct 2021
Blockchain and Federated Edge Learning for Privacy-Preserving Mobile
  Crowdsensing
Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing
Qin Hu
Zhilin Wang
Minghui Xu
Xiuzhen Cheng
32
33
0
16 Oct 2021
FedMe: Federated Learning via Model Exchange
FedMe: Federated Learning via Model Exchange
Koji Matsuda
Yuya Sasaki
Chuan Xiao
Makoto Onizuka
FedML
45
19
0
15 Oct 2021
The Skellam Mechanism for Differentially Private Federated Learning
The Skellam Mechanism for Differentially Private Federated Learning
Naman Agarwal
Peter Kairouz
Ziyu Liu
FedML
11
121
0
11 Oct 2021
Federated Learning for Big Data: A Survey on Opportunities,
  Applications, and Future Directions
Federated Learning for Big Data: A Survey on Opportunities, Applications, and Future Directions
Thippa Reddy Gadekallu
Viet Quoc Pham
Thien Huynh-The
S. Bhattacharya
Praveen Kumar Reddy Maddikunta
Madhusanka Liyanage
FedML
AI4CE
47
39
0
08 Oct 2021
Federated Learning via Plurality Vote
Federated Learning via Plurality Vote
Kai Yue
Richeng Jin
Chau-Wai Wong
H. Dai
FedML
24
8
0
06 Oct 2021
Efficient and Private Federated Learning with Partially Trainable
  Networks
Efficient and Private Federated Learning with Partially Trainable Networks
Hakim Sidahmed
Zheng Xu
Ankush Garg
Yuan Cao
Mingqing Chen
FedML
49
13
0
06 Oct 2021
Communication-Efficient Federated Learning with Binary Neural Networks
Communication-Efficient Federated Learning with Binary Neural Networks
YuZhi Yang
Zhaoyang Zhang
Qianqian Yang
FedML
26
31
0
05 Oct 2021
Towards General-purpose Infrastructure for Protecting Scientific Data
  Under Study
Towards General-purpose Infrastructure for Protecting Scientific Data Under Study
Andrew Trask
Kritika Prakash
41
3
0
04 Oct 2021
UserIdentifier: Implicit User Representations for Simple and Effective
  Personalized Sentiment Analysis
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
Fatemehsadat Mireshghallah
Vaishnavi Shrivastava
Milad Shokouhi
Taylor Berg-Kirkpatrick
Robert Sim
Dimitrios Dimitriadis
FedML
46
33
0
01 Oct 2021
Enforcing fairness in private federated learning via the modified method
  of differential multipliers
Enforcing fairness in private federated learning via the modified method of differential multipliers
Borja Rodríguez Gálvez
Filip Granqvist
Rogier van Dalen
M. Seigel
FedML
45
52
0
17 Sep 2021
Connecting Low-Loss Subspace for Personalized Federated Learning
Connecting Low-Loss Subspace for Personalized Federated Learning
S. Hahn
Minwoo Jeong
Junghye Lee
FedML
24
18
0
16 Sep 2021
Knowledge-Aware Meta-learning for Low-Resource Text Classification
Knowledge-Aware Meta-learning for Low-Resource Text Classification
Huaxiu Yao
Yingxin Wu
Maruan Al-Shedivat
Eric P. Xing
VLM
CLIP
63
11
0
10 Sep 2021
FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo
  Federated Learning
FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning
Zhifeng Jiang
Wen Wang
Yang Liu
FedML
24
49
0
02 Sep 2021
Private Multi-Task Learning: Formulation and Applications to Federated
  Learning
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Shengyuan Hu
Zhiwei Steven Wu
Virginia Smith
FedML
27
19
0
30 Aug 2021
Federated Multi-Task Learning under a Mixture of Distributions
Federated Multi-Task Learning under a Mixture of Distributions
Othmane Marfoq
Giovanni Neglia
A. Bellet
Laetitia Kameni
Richard Vidal
FedML
40
269
0
23 Aug 2021
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