ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2206.10963
  4. Cited By
FLaaS: Cross-App On-device Federated Learning in Mobile Environments

FLaaS: Cross-App On-device Federated Learning in Mobile Environments

22 June 2022
Kleomenis Katevas
Diego Perino
N. Kourtellis
    FedML
ArXivPDFHTML

Papers citing "FLaaS: Cross-App On-device Federated Learning in Mobile Environments"

20 / 20 papers shown
Title
On-device Federated Learning in Smartphones for Detecting Depression from Reddit Posts
On-device Federated Learning in Smartphones for Detecting Depression from Reddit Posts
Mustofa Ahmed
Abdul Muntakim
Nawrin Tabassum
Mohammad Asifur Rahim
Faisal Muhammad Shah
FedML
64
1
0
17 Oct 2024
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
140
139
0
08 Nov 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
99
278
0
23 Aug 2021
PPFL: Privacy-preserving Federated Learning with Trusted Execution
  Environments
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
Fan Mo
Hamed Haddadi
Kleomenis Katevas
Eduard Marin
Diego Perino
N. Kourtellis
FedML
106
246
0
29 Apr 2021
On-device Federated Learning with Flower
On-device Federated Learning with Flower
Akhil Mathur
Daniel J. Beutel
Pedro Porto Buarque de Gusmão
Javier Fernandez-Marques
Taner Topal
Xinchi Qiu
Titouan Parcollet
Yan Gao
Nicholas D. Lane
FedML
84
38
0
07 Apr 2021
Federated Evaluation and Tuning for On-Device Personalization: System
  Design & Applications
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
Matthias Paulik
M. Seigel
Henry Mason
Dominic Telaar
Joris Kluivers
...
Dominic Hughes
O. Javidbakht
Fei Dong
Rehan Rishi
Stanley Hung
FedML
244
127
0
16 Feb 2021
FLaaS: Federated Learning as a Service
FLaaS: Federated Learning as a Service
N. Kourtellis
Kleomenis Katevas
Diego Perino
FedML
40
60
0
18 Nov 2020
FedML: A Research Library and Benchmark for Federated Machine Learning
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He
Songze Li
Jinhyun So
Xiao Zeng
Mi Zhang
...
Yang Liu
Ramesh Raskar
Qiang Yang
M. Annavaram
Salman Avestimehr
FedML
226
577
0
27 Jul 2020
BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices
BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices
Matteo Varvello
Kleomenis Katevas
Mihai Plesa
Hamed Haddadi
B. Livshits
17
14
0
20 Oct 2019
White-box vs Black-box: Bayes Optimal Strategies for Membership
  Inference
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference
Alexandre Sablayrolles
Matthijs Douze
Yann Ollivier
Cordelia Schmid
Hervé Jégou
MIACV
64
366
0
29 Aug 2019
Variational Federated Multi-Task Learning
Variational Federated Multi-Task Learning
Luca Corinzia
Ami Beuret
J. M. Buhmann
FedML
63
161
0
14 Jun 2019
Towards Federated Learning at Scale: System Design
Towards Federated Learning at Scale: System Design
Keith Bonawitz
Hubert Eichner
W. Grieskamp
Dzmitry Huba
A. Ingerman
...
H. B. McMahan
Timon Van Overveldt
David Petrou
Daniel Ramage
Jason Roselander
FedML
121
2,664
0
04 Feb 2019
LEAF: A Benchmark for Federated Settings
LEAF: A Benchmark for Federated Settings
S. Caldas
Sai Meher Karthik Duddu
Peter Wu
Tian Li
Jakub Konecný
H. B. McMahan
Virginia Smith
Ameet Talwalkar
FedML
137
1,419
0
03 Dec 2018
Exploiting Unintended Feature Leakage in Collaborative Learning
Exploiting Unintended Feature Leakage in Collaborative Learning
Luca Melis
Congzheng Song
Emiliano De Cristofaro
Vitaly Shmatikov
FedML
142
1,474
0
10 May 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler
Andrew G. Howard
Menglong Zhu
A. Zhmoginov
Liang-Chieh Chen
178
19,271
0
13 Jan 2018
Differentially Private Federated Learning: A Client Level Perspective
Differentially Private Federated Learning: A Client Level Perspective
Robin C. Geyer
T. Klein
Moin Nabi
FedML
116
1,294
0
20 Dec 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep
  Learning
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
Briland Hitaj
G. Ateniese
Fernando Perez-Cruz
FedML
115
1,401
0
24 Feb 2017
Membership Inference Attacks against Machine Learning Models
Membership Inference Attacks against Machine Learning Models
Reza Shokri
M. Stronati
Congzheng Song
Vitaly Shmatikov
SLR
MIALM
MIACV
246
4,122
0
18 Oct 2016
Federated Learning: Strategies for Improving Communication Efficiency
Federated Learning: Strategies for Improving Communication Efficiency
Jakub Konecný
H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
FedML
293
4,643
0
18 Oct 2016
Communication-Efficient Learning of Deep Networks from Decentralized
  Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
397
17,468
0
17 Feb 2016
1