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Advances and Open Problems in Federated Learning

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 E. 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
D. Song
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
    FedML
    AI4CE
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Papers citing "Advances and Open Problems in Federated Learning"

50 / 857 papers shown
Title
Federated Minimax Optimization: Improved Convergence Analyses and
  Algorithms
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms
Pranay Sharma
Rohan Panda
Gauri Joshi
P. Varshney
FedML
19
46
0
09 Mar 2022
Distributed Riemannian Optimization with Lazy Communication for
  Collaborative Geometric Estimation
Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation
Yulun Tian
Amrit Singh Bedi
Alec Koppel
Miguel Calvo-Fullana
David M. Rosen
Jonathan P. How
22
5
0
02 Mar 2022
FedDrive: Generalizing Federated Learning to Semantic Segmentation in
  Autonomous Driving
FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving
Lidia Fantauzzo
Eros Fani
Debora Caldarola
A. Tavera
Fabio Cermelli
Marco Ciccone
Barbara Caputo
FedML
21
52
0
28 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
11
1
0
23 Feb 2022
Degree-Preserving Randomized Response for Graph Neural Networks under
  Local Differential Privacy
Degree-Preserving Randomized Response for Graph Neural Networks under Local Differential Privacy
Seira Hidano
Takao Murakami
24
8
0
21 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
14
56
0
18 Feb 2022
FLAME: Federated Learning Across Multi-device Environments
FLAME: Federated Learning Across Multi-device Environments
Hyunsung Cho
Akhil Mathur
F. Kawsar
11
21
0
17 Feb 2022
Single-shot Hyper-parameter Optimization for Federated Learning: A
  General Algorithm & Analysis
Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis
Yi Zhou
Parikshit Ram
Theodoros Salonidis
Nathalie Baracaldo
Horst Samulowitz
Heiko Ludwig
FedML
24
6
0
16 Feb 2022
Evaluation and Analysis of Different Aggregation and Hyperparameter
  Selection Methods for Federated Brain Tumor Segmentation
Evaluation and Analysis of Different Aggregation and Hyperparameter Selection Methods for Federated Brain Tumor Segmentation
Ece Isik Polat
Gorkem Polat
Altan Koçyiğit
A. Temi̇zel
OOD
FedML
22
3
0
16 Feb 2022
Federated Contrastive Learning for Dermatological Disease Diagnosis via
  On-device Learning
Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning
Yawen Wu
Dewen Zeng
Zhepeng Wang
Yi Sheng
Lei Yang
A. James
Yiyu Shi
Jingtong Hu
FedML
16
31
0
14 Feb 2022
On the Convergence of Clustered Federated Learning
On the Convergence of Clustered Federated Learning
Ma Jie
Guodong Long
Tianyi Zhou
Jing Jiang
Chengqi Zhang
FedML
31
46
0
13 Feb 2022
Private Adaptive Optimization with Side Information
Private Adaptive Optimization with Side Information
Tian Li
Manzil Zaheer
Sashank J. Reddi
Virginia Smith
24
35
0
12 Feb 2022
SHED: A Newton-type algorithm for federated learning based on
  incremental Hessian eigenvector sharing
SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing
Nicolò Dal Fabbro
S. Dey
M. Rossi
Luca Schenato
FedML
29
14
0
11 Feb 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated
  Learning
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning
A. Bietti
Chen-Yu Wei
Miroslav Dudík
John Langford
Zhiwei Steven Wu
FedML
20
43
0
10 Feb 2022
Adaptive and Robust Multi-Task Learning
Adaptive and Robust Multi-Task Learning
Yaqi Duan
Kaizheng Wang
75
23
0
10 Feb 2022
Identifying Backdoor Attacks in Federated Learning via Anomaly Detection
Identifying Backdoor Attacks in Federated Learning via Anomaly Detection
Yuxi Mi
Yiheng Sun
Jihong Guan
Shuigeng Zhou
AAML
FedML
11
1
0
09 Feb 2022
Practical Challenges in Differentially-Private Federated Survival
  Analysis of Medical Data
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
Shadi Rahimian
Raouf Kerkouche
I. Kurth
Mario Fritz
FedML
8
11
0
08 Feb 2022
More is Better (Mostly): On the Backdoor Attacks in Federated Graph
  Neural Networks
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks
Jing Xu
Rui Wang
Stefanos Koffas
K. Liang
S. Picek
FedML
AAML
31
25
0
07 Feb 2022
Addressing modern and practical challenges in machine learning: A survey
  of online federated and transfer learning
Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning
Shuang Dai
Fanlin Meng
FedML
OnRL
32
21
0
07 Feb 2022
CECILIA: Comprehensive Secure Machine Learning Framework
CECILIA: Comprehensive Secure Machine Learning Framework
Ali Burak Ünal
Nícolas Pfeifer
Mete Akgun
25
2
0
07 Feb 2022
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
D. Kovalev
Aleksandr Beznosikov
Abdurakhmon Sadiev
Michael Persiianov
Peter Richtárik
Alexander Gasnikov
35
34
0
06 Feb 2022
Distributed Learning With Sparsified Gradient Differences
Distributed Learning With Sparsified Gradient Differences
Yicheng Chen
Rick S. Blum
Martin Takáč
Brian M. Sadler
18
15
0
05 Feb 2022
Training Differentially Private Models with Secure Multiparty Computation
Training Differentially Private Models with Secure Multiparty Computation
Sikha Pentyala
Davis Railsback
Ricardo Maia
Rafael Dowsley
David Melanson
Anderson C. A. Nascimento
Martine De Cock
11
14
0
05 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
14
6
0
03 Feb 2022
Causal Inference Through the Structural Causal Marginal Problem
Causal Inference Through the Structural Causal Marginal Problem
Luigi Gresele
Julius von Kügelgen
Jonas M. Kubler
Elke Kirschbaum
Bernhard Schölkopf
Dominik Janzing
22
19
0
02 Feb 2022
FedSpace: An Efficient Federated Learning Framework at Satellites and
  Ground Stations
FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations
Jinhyun So
Kevin Hsieh
Behnaz Arzani
Shadi Noghabi
Salman Avestimehr
Ranveer Chandra
FedML
6
60
0
02 Feb 2022
Communication Efficient Federated Learning for Generalized Linear
  Bandits
Communication Efficient Federated Learning for Generalized Linear Bandits
Chuanhao Li
Hongning Wang
FedML
22
13
0
02 Feb 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient
  Magnification
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
Yuxin Wen
Jonas Geiping
Liam H. Fowl
Micah Goldblum
Tom Goldstein
FedML
79
92
0
01 Feb 2022
Federated Active Learning (F-AL): an Efficient Annotation Strategy for
  Federated Learning
Federated Active Learning (F-AL): an Efficient Annotation Strategy for Federated Learning
J. Ahn
Yeeun Ma
Seoyun Park
Cheolwoo You
FedML
37
22
0
01 Feb 2022
Challenges and approaches to privacy preserving post-click conversion
  prediction
Challenges and approaches to privacy preserving post-click conversion prediction
Conor O'Brien
Arvind Thiagarajan
Sourav Das
Rafael Barreto
C. Verma
Tim Hsu
James Neufeld
Jonathan J. Hunt
OffRL
11
10
0
29 Jan 2022
Improving Federated Learning Face Recognition via Privacy-Agnostic
  Clusters
Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters
Qiang Meng
Feng Zhou
Hainan Ren
Tianshu Feng
Guochao Liu
Yuanqing Lin
FedML
17
38
0
29 Jan 2022
Speeding up Heterogeneous Federated Learning with Sequentially Trained
  Superclients
Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients
Riccardo Zaccone
Andrea Rizzardi
Debora Caldarola
Marco Ciccone
Barbara Caputo
FedML
48
14
0
26 Jan 2022
Towards Multi-Objective Statistically Fair Federated Learning
Towards Multi-Objective Statistically Fair Federated Learning
Ninareh Mehrabi
Cyprien de Lichy
John McKay
C. He
William Campbell
FedML
17
9
0
24 Jan 2022
Long-term Data Sharing under Exclusivity Attacks
Long-term Data Sharing under Exclusivity Attacks
Yotam gafni
Moshe Tennenholtz
12
2
0
22 Jan 2022
FedComm: Federated Learning as a Medium for Covert Communication
FedComm: Federated Learning as a Medium for Covert Communication
Dorjan Hitaj
Giulio Pagnotta
B. Hitaj
F. Pérez-Cruz
L. Mancini
FedML
25
10
0
21 Jan 2022
TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates
  into Gradients from Proxy Data
TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data
Isha Garg
M. Nagaraj
Kaushik Roy
FedML
15
1
0
21 Jan 2022
Federated Learning with Heterogeneous Architectures using Graph
  HyperNetworks
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
Or Litany
Haggai Maron
David Acuna
Jan Kautz
Gal Chechik
Sanja Fidler
FedML
28
24
0
20 Jan 2022
Caring Without Sharing: A Federated Learning Crowdsensing Framework for
  Diversifying Representation of Cities
Caring Without Sharing: A Federated Learning Crowdsensing Framework for Diversifying Representation of Cities
Mi-Gyoung Cho
A. Mashhadi
FedML
23
1
0
20 Jan 2022
SCOTCH: An Efficient Secure Computation Framework for Secure Aggregation
SCOTCH: An Efficient Secure Computation Framework for Secure Aggregation
Yash More
Prashanthi Ramachandran
Priyam Panda
A. Mondal
Harpreet Virk
Debayan Gupta
FedML
11
11
0
19 Jan 2022
Towards Federated Clustering: A Federated Fuzzy $c$-Means Algorithm
  (FFCM)
Towards Federated Clustering: A Federated Fuzzy ccc-Means Algorithm (FFCM)
Morris Stallmann
A. Wilbik
FedML
30
37
0
18 Jan 2022
How to Backdoor HyperNetwork in Personalized Federated Learning?
How to Backdoor HyperNetwork in Personalized Federated Learning?
Phung Lai
Nhathai Phan
Issa M. Khalil
Abdallah Khreishah
Xintao Wu
AAML
FedML
23
0
0
18 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
13
13
0
10 Jan 2022
Fair and efficient contribution valuation for vertical federated
  learning
Fair and efficient contribution valuation for vertical federated learning
Zhenan Fan
Huang Fang
Zirui Zhou
Jian Pei
M. Friedlander
Yong Zhang
TDI
FedML
11
25
0
07 Jan 2022
Federated Optimization of Smooth Loss Functions
Federated Optimization of Smooth Loss Functions
Ali Jadbabaie
A. Makur
Devavrat Shah
FedML
17
7
0
06 Jan 2022
Secret Sharing Sharing For Highly Scalable Secure Aggregation
Secret Sharing Sharing For Highly Scalable Secure Aggregation
Timothy Stevens
Joseph P. Near
Christian Skalka
FedML
14
5
0
03 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
Zhiqiang Zhang
Jun Zhou
Chaochao Chen
FedML
26
10
0
28 Dec 2021
Robust Convergence in Federated Learning through Label-wise Clustering
Robust Convergence in Federated Learning through Label-wise Clustering
Hunmin Lee
Yueyang Liu
Donghyun Kim
Yingshu Li
FedML
17
1
0
28 Dec 2021
Attribute Inference Attack of Speech Emotion Recognition in Federated
  Learning Settings
Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Settings
Tiantian Feng
H. Hashemi
Rajat Hebbar
M. Annavaram
Shrikanth S. Narayanan
13
25
0
26 Dec 2021
Towards Federated Learning on Time-Evolving Heterogeneous Data
Towards Federated Learning on Time-Evolving Heterogeneous Data
Yongxin Guo
Tao R. Lin
Xiaoying Tang
FedML
14
30
0
25 Dec 2021
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning
Irem Ergun
Hasin Us Sami
Başak Güler
FedML
28
25
0
23 Dec 2021
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