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Advances and Open Problems in Federated Learning
v1v2v3 (latest)

Advances and Open Problems in Federated Learning

10 December 2019
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
A. Bhagoji
Keith Bonawitz
Zachary B. Charles
Graham Cormode
Rachel Cummings
Rafael G. L. DÓliveira
Hubert Eichner
S. E. Rouayheb
David Evans
Josh Gardner
Zachary Garrett
Adria Gascon
Badih Ghazi
Phillip B. Gibbons
Marco Gruteser
Zaïd Harchaoui
Chaoyang He
Lie He
Zhouyuan Huo
Ben Hutchinson
Justin Hsu
Martin Jaggi
T. Javidi
Gauri Joshi
M. Khodak
Jakub Konecný
Aleksandra Korolova
F. Koushanfar
Oluwasanmi Koyejo
Tancrède Lepoint
Yang Liu
Prateek Mittal
M. Mohri
Richard Nock
A. Özgür
Rasmus Pagh
Mariana Raykova
Hang Qi
Daniel Ramage
Ramesh Raskar
Basel Alomair
Weikang Song
Sebastian U. Stich
Ziteng Sun
A. Suresh
Florian Tramèr
Praneeth Vepakomma
Jianyu Wang
Li Xiong
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
    FedMLAI4CE
ArXiv (abs)PDFHTML

Papers citing "Advances and Open Problems in Federated Learning"

50 / 2,962 papers shown
Improved Communication Efficiency in Federated Natural Policy Gradient
  via ADMM-based Gradient Updates
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient UpdatesNeural Information Processing Systems (NeurIPS), 2023
Guangchen Lan
Han Wang
James Anderson
Christopher G. Brinton
Vaneet Aggarwal
FedML
281
31
0
09 Oct 2023
Little is Enough: Improving Privacy by Sharing Labels in Federated
  Semi-Supervised Learning
Little is Enough: Improving Privacy by Sharing Labels in Federated Semi-Supervised LearningAAAI Conference on Artificial Intelligence (AAAI), 2023
Amr Abourayya
Jens Kleesiek
Kanishka Rao
Erman Ayday
Bharat Rao
Geoff Webb
Michael Kamp
FedML
294
1
0
09 Oct 2023
On the Convergence of Federated Averaging under Partial Participation
  for Over-parameterized Neural Networks
On the Convergence of Federated Averaging under Partial Participation for Over-parameterized Neural Networks
Xin Liu
Wei Tao
Dazhi Zhan
Yu Pan
Xin Ma
Yu Ding
Zhisong Pan
FedML
261
0
0
09 Oct 2023
RECESS Vaccine for Federated Learning: Proactive Defense Against Model
  Poisoning Attacks
RECESS Vaccine for Federated Learning: Proactive Defense Against Model Poisoning AttacksNeural Information Processing Systems (NeurIPS), 2023
Haonan Yan
Wenjing Zhang
Qian Chen
Xiaoguang Li
Wenhai Sun
Hui Li
Xiao-La Lin
AAML
131
14
0
09 Oct 2023
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and
  Applications
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and ApplicationsComputer Communications (Comput. Commun.), 2023
Azim Akhtarshenas
Mohammad Ali Vahedifar
Navid Ayoobi
B. Maham
Tohid Alizadeh
Sina Ebrahimi
David López-Pérez
FedML
249
18
0
08 Oct 2023
FedFed: Feature Distillation against Data Heterogeneity in Federated
  Learning
FedFed: Feature Distillation against Data Heterogeneity in Federated LearningNeural Information Processing Systems (NeurIPS), 2023
Zhiqin Yang
Yonggang Zhang
Yuxiang Zheng
Xinmei Tian
Hao Peng
Tongliang Liu
Bo Han
FedML
198
115
0
08 Oct 2023
Profit: Benchmarking Personalization and Robustness Trade-off in
  Federated Prompt Tuning
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning
Liam Collins
Shanshan Wu
Sewoong Oh
K. Sim
FedML
276
11
0
06 Oct 2023
Privacy-Preserving Financial Anomaly Detection via Federated Learning &
  Multi-Party Computation
Privacy-Preserving Financial Anomaly Detection via Federated Learning & Multi-Party Computation
Sunpreet S. Arora
Andrew Beams
Panagiotis Chatzigiannis
Sebastian Meiser
Karan Patel
...
Harshal Shah
Yizhen Wang
Yuhang Wu
Hao Yang
Mahdi Zamani
FedML
181
10
0
06 Oct 2023
Utilizing Free Clients in Federated Learning for Focused Model
  Enhancement
Utilizing Free Clients in Federated Learning for Focused Model Enhancement
Aditya Narayan Ravi
Ilan Shomorony
FedML
272
0
0
06 Oct 2023
FLAIM: AIM-based Synthetic Data Generation in the Federated Setting
FLAIM: AIM-based Synthetic Data Generation in the Federated SettingKnowledge Discovery and Data Mining (KDD), 2023
Samuel Maddock
Graham Cormode
Carsten Maple
261
5
0
05 Oct 2023
FedNAR: Federated Optimization with Normalized Annealing Regularization
FedNAR: Federated Optimization with Normalized Annealing RegularizationNeural Information Processing Systems (NeurIPS), 2023
Junbo Li
Ang Li
Chong Tian
Qirong Ho
Eric Xing
Hongyi Wang
FedML
144
7
0
04 Oct 2023
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated
  Learning with Hypergradient Descent
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient DescentInternational Conference on Learning Representations (ICLR), 2023
Ziyao Wang
Jianyu Wang
Ang Li
FedML
282
6
0
04 Oct 2023
Exploring the Impact of Disrupted Peer-to-Peer Communications on Fully
  Decentralized Learning in Disaster Scenarios
Exploring the Impact of Disrupted Peer-to-Peer Communications on Fully Decentralized Learning in Disaster ScenariosInternational Conference on Information and Communication Technologies for Disaster Management (ICT-DM), 2023
Luigi Palmieri
Chiara Boldrini
Lorenzo Valerio
A. Passarella
M. Conti
187
7
0
04 Oct 2023
Recent Methodological Advances in Federated Learning for Healthcare
Recent Methodological Advances in Federated Learning for Healthcare
Fan Zhang
Daniel Kreuter
Yichen Chen
Sören Dittmer
Samuel Tull
...
James H. F. Rudd
J. A. Aston
Carola-Bibiane Schönlieb
Nicholas S. Gleadall
Michael Roberts
FedMLOOD
196
21
0
04 Oct 2023
Inclusive Data Representation in Federated Learning: A Novel Approach
  Integrating Textual and Visual Prompt
Inclusive Data Representation in Federated Learning: A Novel Approach Integrating Textual and Visual Prompt
Zihao Zhao
Zhenpeng Shi
Yang Liu
Wenbo Ding
FedML
253
1
0
04 Oct 2023
Enhanced Federated Optimization: Adaptive Unbiased Sampling with Reduced
  Variance
Enhanced Federated Optimization: Adaptive Unbiased Sampling with Reduced Variance
Dun Zeng
Zenglin Xu
Yu Pan
Xu Luo
Qifan Wang
Xiaoying Tang
FedML
278
1
0
04 Oct 2023
FedL2P: Federated Learning to Personalize
FedL2P: Federated Learning to PersonalizeNeural Information Processing Systems (NeurIPS), 2023
Royson Lee
Minyoung Kim
Da Li
Xinchi Qiu
Timothy M. Hospedales
Ferenc Huszár
Nicholas D. Lane
FedML
158
0
0
03 Oct 2023
FLEDGE: Ledger-based Federated Learning Resilient to Inference and
  Backdoor Attacks
FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor AttacksAsia-Pacific Computer Systems Architecture Conference (ACSA), 2023
Jorge Castillo
Phillip Rieger
Hossein Fereidooni
Qian Chen
Ahmad Sadeghi
FedMLAAML
158
10
0
03 Oct 2023
Federated Wasserstein Distance
Federated Wasserstein DistanceInternational Conference on Learning Representations (ICLR), 2023
Alain Rakotomamonjy
Kimia Nadjahi
L. Ralaivola
239
9
0
03 Oct 2023
Epidemic Learning: Boosting Decentralized Learning with Randomized
  Communication
Epidemic Learning: Boosting Decentralized Learning with Randomized CommunicationNeural Information Processing Systems (NeurIPS), 2023
M. Vos
Sadegh Farhadkhani
R. Guerraoui
Anne-Marie Kermarrec
Rafael Pires
Rishi Sharma
310
25
0
03 Oct 2023
Fusing Models with Complementary Expertise
Fusing Models with Complementary ExpertiseInternational Conference on Learning Representations (ICLR), 2023
Hongyi Wang
Felipe Maia Polo
Yuekai Sun
Souvik Kundu
Eric Xing
Mikhail Yurochkin
FedMLMoMe
467
39
0
02 Oct 2023
Adversarial Client Detection via Non-parametric Subspace Monitoring in
  the Internet of Federated Things
Adversarial Client Detection via Non-parametric Subspace Monitoring in the Internet of Federated ThingsIISE Transactions (IISE Trans.), 2023
Xianjian Xie
Xiaochen Xian
Dan Li
Andi Wang
155
0
0
02 Oct 2023
Window-based Model Averaging Improves Generalization in Heterogeneous
  Federated Learning
Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning
Debora Caldarola
Barbara Caputo
Marco Ciccone
FedML
257
8
0
02 Oct 2023
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language
  Models
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language ModelsInternational Conference on Machine Learning (ICML), 2023
Jingwei Sun
Ziyue Xu
Hongxu Yin
Dong Yang
Daguang Xu
Yiran Chen
Holger R. Roth
VLM
272
34
0
02 Oct 2023
FedLPA: One-shot Federated Learning with Layer-Wise Posterior
  Aggregation
FedLPA: One-shot Federated Learning with Layer-Wise Posterior AggregationNeural Information Processing Systems (NeurIPS), 2023
Xiang Liu
Liangxi Liu
Feiyang Ye
Yunheng Shen
Xia Li
Linshan Jiang
Jialin Li
473
13
0
30 Sep 2023
FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of
  Things
FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things
Samiul Alam
Tuo Zhang
Tiantian Feng
Hui Shen
Zhichao Cao
...
JeongGil Ko
Kiran Somasundaram
Shrikanth S. Narayanan
Salman Avestimehr
Mi Zhang
385
13
0
29 Sep 2023
Benchmarking Collaborative Learning Methods Cost-Effectiveness for
  Prostate Segmentation
Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation
Lucia Innocenti
Michela Antonelli
Francesco Cremonesi
Kenaan Sarhan
Alejandro Granados
Vicky Goh
Sebastien Ourselin
Marco Lorenzi
FedML
215
2
0
29 Sep 2023
Mode Connectivity and Data Heterogeneity of Federated Learning
Mode Connectivity and Data Heterogeneity of Federated Learning
Tailin Zhou
Jun Zhang
Danny H. K. Tsang
FedML
241
5
0
29 Sep 2023
Collaborative Distributed Machine Learning
Collaborative Distributed Machine LearningACM Computing Surveys (ACM Comput. Surv.), 2023
Sumit Kumar Jha
Patrick Lincoln
Sascha Rank
Ali Sunyaev
394
5
0
28 Sep 2023
Generalizable Heterogeneous Federated Cross-Correlation and Instance
  Similarity Learning
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity LearningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Wenke Huang
J. J. Valero-Mas
Dasaem Jeong
Bo Du
FedML
224
80
0
28 Sep 2023
Deep Model Fusion: A Survey
Deep Model Fusion: A Survey
Weishi Li
Yong Peng
Miao Zhang
Liang Ding
Han Hu
Li Shen
FedMLMoMe
302
87
0
27 Sep 2023
Genetic Algorithm-Based Dynamic Backdoor Attack on Federated
  Learning-Based Network Traffic Classification
Genetic Algorithm-Based Dynamic Backdoor Attack on Federated Learning-Based Network Traffic ClassificationInternational Conference on Fog and Mobile Edge Computing (FMEC), 2023
Mahmoud Nazzal
Nura Aljaafari
Ahmad H. Sawalmeh
Abdallah Khreishah
Muhammad Anan
...
Mohammed Alnaeem
Adel Aldalbahi
Abdulaziz Alhumam
C. Vizcarra
Shadan Alhamed
AAML
92
0
0
27 Sep 2023
Multi-dimensional Data Quick Query for Blockchain-based Federated
  Learning
Multi-dimensional Data Quick Query for Blockchain-based Federated LearningWireless Algorithms, Systems, and Applications (WASA), 2023
Jiaxi Yang
Sheng Cao
Xiangli Peng
Xiong-da Li
Xiaosong Zhang
122
2
0
27 Sep 2023
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous
  Client Devices using a Computing Power Aware Scheduler
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware SchedulerInternational Conference on Learning Representations (ICLR), 2023
Zilinghan Li
Pranshu Chaturvedi
Shilan He
Han-qiu Chen
Gagandeep Singh
Volodymyr V. Kindratenko
Eliu A. Huerta
Kibaek Kim
Ravi K. Madduri
FedML
270
17
0
26 Sep 2023
Byzantine-Resilient Federated PCA and Low Rank Column-wise Sensing
Byzantine-Resilient Federated PCA and Low Rank Column-wise SensingIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023
Ankit Pratap Singh
Namrata Vaswani
423
1
0
25 Sep 2023
Federated Learning Under Restricted User Availability
Federated Learning Under Restricted User AvailabilityIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Periklis Theodoropoulos
Konstantinos E. Nikolakakis
Dionysios S. Kalogerias
FedML
124
4
0
25 Sep 2023
REPA: Client Clustering without Training and Data Labels for Improved
  Federated Learning in Non-IID Settings
REPA: Client Clustering without Training and Data Labels for Improved Federated Learning in Non-IID Settings
Boris Radovic
Veljko Pejović
FedML
157
5
0
25 Sep 2023
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated
  Learning
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated LearningNeural Information Processing Systems (NeurIPS), 2023
Kangyang Luo
Shuai Wang
Y. Fu
Xiang Li
Yunshi Lan
Minghui Gao
FedML
239
48
0
24 Sep 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
93
0
0
21 Sep 2023
Preconditioned Federated Learning
Preconditioned Federated Learning
Zeyi Tao
Jindi Wu
Qun Li
FedML
95
1
0
20 Sep 2023
SPFL: A Self-purified Federated Learning Method Against Poisoning
  Attacks
SPFL: A Self-purified Federated Learning Method Against Poisoning AttacksIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2023
Zizhen Liu
Weiyang He
Chip-Hong Chang
Jing Ye
Huawei Li
Xiaowei Li
242
10
0
19 Sep 2023
FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup
  for Non-IID Data
FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data
Hao Sun
Li Shen
Shi-Yong Chen
Jingwei Sun
Jing Li
Guangzhong Sun
Dacheng Tao
FedML
202
2
0
18 Sep 2023
FedGKD: Unleashing the Power of Collaboration in Federated Graph Neural
  Networks
FedGKD: Unleashing the Power of Collaboration in Federated Graph Neural Networks
Qiying Pan
Ruofan Wu
Tengfei Liu
Tianyi Zhang
Yifei Zhu
Weiqiang Wang
FedML
279
10
0
18 Sep 2023
UNIDEAL: Curriculum Knowledge Distillation Federated Learning
UNIDEAL: Curriculum Knowledge Distillation Federated LearningIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Yuwen Yang
Shaokai Wu
Xun Cai
Wei Ji
Hongtao Lu
Yue Ding
FedML
229
11
0
16 Sep 2023
FedFNN: Faster Training Convergence Through Update Predictions in
  Federated Recommender Systems
FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems
Francesco Fabbri
Xianghang Liu
Jack R. McKenzie
Bartlomiej Twardowski
Tri Kurniawan Wijaya
FedML
173
0
0
14 Sep 2023
Mitigating Adversarial Attacks in Federated Learning with Trusted
  Execution Environments
Mitigating Adversarial Attacks in Federated Learning with Trusted Execution EnvironmentsIEEE International Conference on Distributed Computing Systems (ICDCS), 2023
Simon Queyrut
V. Schiavoni
Pascal Felber
AAMLFedML
209
15
0
13 Sep 2023
Fingerprint Attack: Client De-Anonymization in Federated Learning
Fingerprint Attack: Client De-Anonymization in Federated LearningEuropean Conference on Artificial Intelligence (ECAI), 2023
Xingliang Yuan
Trevor Cohn
Olga Ohrimenko
FedML
181
2
0
12 Sep 2023
Advancing Federated Learning in 6G: A Trusted Architecture with
  Graph-based Analysis
Advancing Federated Learning in 6G: A Trusted Architecture with Graph-based AnalysisGlobal Communications Conference (GLOBECOM), 2023
Wenxuan Ye
Chendi Qian
Xueli An
Xueqiang Yan
Georg Carle
FedML
289
12
0
11 Sep 2023
Towards Federated Learning Under Resource Constraints via Layer-wise
  Training and Depth Dropout
Towards Federated Learning Under Resource Constraints via Layer-wise Training and Depth Dropout
Pengfei Guo
Warren Morningstar
Raviteja Vemulapalli
K. Singhal
Vishal M. Patel
Philip Mansfield
FedML
276
5
0
11 Sep 2023
Privacy Preserving Federated Learning with Convolutional Variational
  Bottlenecks
Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks
Daniel Scheliga
Patrick Mäder
M. Seeland
FedMLAAML
331
8
0
08 Sep 2023
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