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. 1811.04017
  4. Cited By
A generic framework for privacy preserving deep learning

A generic framework for privacy preserving deep learning

9 November 2018
Wenbo Guo
Yunzhe Tao
Morten Dahl
Sui Huang
Masashi Sugiyama
Daniel Rueckert
Lin Lin
    FedML
ArXivPDFHTML

Papers citing "A generic framework for privacy preserving deep learning"

50 / 166 papers shown
Title
A Federated Random Forest Solution for Secure Distributed Machine Learning
A Federated Random Forest Solution for Secure Distributed Machine Learning
Alexandre Cotorobai
Jorge Miguel Silva
Jose Luis Oliveira
OOD
FedML
37
0
0
12 May 2025
BlindFL: Segmented Federated Learning with Fully Homomorphic Encryption
BlindFL: Segmented Federated Learning with Fully Homomorphic Encryption
Evan Gronberg
L. dÁliberti
Magnus Saebo
Aurora Hook
FedML
56
0
0
20 Jan 2025
Assistive AI for Augmenting Human Decision-making
Assistive AI for Augmenting Human Decision-making
Natabara Máté Gyöngyössy
Bernát Török
Csilla Farkas
Laura Lucaj
Attila Menyhárd
Krisztina Menyhárd-Balázs
András Simonyi
Patrick van der Smagt
Zsolt Ződi
András Lőrincz
41
0
0
18 Oct 2024
From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare
From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare
Ming Li
Pengcheng Xu
Junjie Hu
Zeyu Tang
Guang Yang
FedML
50
1
0
15 Sep 2024
FedModule: A Modular Federated Learning Framework
FedModule: A Modular Federated Learning Framework
Chuyi Chen
Zhe Zhang
Yanchao Zhao
FedML
28
0
0
07 Sep 2024
COALA: A Practical and Vision-Centric Federated Learning Platform
COALA: A Practical and Vision-Centric Federated Learning Platform
Weiming Zhuang
Jian Xu
Chen Chen
Jingtao Li
Lingjuan Lyu
VLM
FedML
79
4
0
23 Jul 2024
Federated Computing -- Survey on Building Blocks, Extensions and Systems
Federated Computing -- Survey on Building Blocks, Extensions and Systems
René Schwermer
R. Mayer
Hans-Arno Jacobsen
FedML
43
1
0
03 Apr 2024
Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and
  Insights
Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights
Maryam Ben Driss
Essaid Sabir
H. Elbiaze
Walid Saad
41
7
0
07 Dec 2023
zkDFL: An efficient and privacy-preserving decentralized federated
  learning with zero-knowledge proof
zkDFL: An efficient and privacy-preserving decentralized federated learning with zero-knowledge proof
Mojtaba Ahmadi
Reza Nourmohammadi
27
7
0
01 Dec 2023
Edge AI for Internet of Energy: Challenges and Perspectives
Edge AI for Internet of Energy: Challenges and Perspectives
Yassine Himeur
A. Sayed
A. Alsalemi
F. Bensaali
Abbes Amira
57
26
0
28 Nov 2023
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning
Tianyuan Zou
Zixuan Gu
Yuanqin He
Hideaki Takahashi
Yang Liu
Ya-Qin Zhang
FedML
43
5
0
15 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
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large
  Language Models in Federated Learning
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning
Weirui Kuang
Bingchen Qian
Zitao Li
Daoyuan Chen
Dawei Gao
Xuchen Pan
Yuexiang Xie
Yaliang Li
Bolin Ding
Jingren Zhou
FedML
35
115
0
01 Sep 2023
A Comprehensive Empirical Study of Bugs in Open-Source Federated
  Learning Frameworks
A Comprehensive Empirical Study of Bugs in Open-Source Federated Learning Frameworks
Weijie Shao
Yuyang Gao
Fu Song
Sen Chen
Lingling Fan
JingZhu He
FedML
36
0
0
09 Aug 2023
FLGo: A Fully Customizable Federated Learning Platform
FLGo: A Fully Customizable Federated Learning Platform
Zhilin Wang
Xiaoliang Fan
Zhaopeng Peng
Xueheng Li
Ziqi Yang
Mingkuan Feng
Zhicheng Yang
Xiao Liu
Cheng-i Wang
FedML
32
11
0
21 Jun 2023
FedHC: A Scalable Federated Learning Framework for Heterogeneous and
  Resource-Constrained Clients
FedHC: A Scalable Federated Learning Framework for Heterogeneous and Resource-Constrained Clients
Hao Fei
Fuxun Yu
Yongbo Yu
Minjia Zhang
Ang Li
Xiang Chen
FedML
27
2
0
25 May 2023
Flame: Simplifying Topology Extension in Federated Learning
Flame: Simplifying Topology Extension in Federated Learning
Harshit Daga
Jae-Kwang Shin
D. Garg
Ada Gavrilovska
Myungjin Lee
Ramana Rao Kompella
AI4CE
36
10
0
09 May 2023
MLHOps: Machine Learning for Healthcare Operations
MLHOps: Machine Learning for Healthcare Operations
Kristoffer Larsen
Vallijah Subasri
A. Krishnan
Cláudio Tinoco Mesquita
Diana Paez
Laleh Seyyed-Kalantari
Amalia Peix
LM&MA
AI4TS
VLM
32
2
0
04 May 2023
Fed-BioMed: Open, Transparent and Trusted Federated Learning for
  Real-world Healthcare Applications
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
Francesco Cremonesi
Marc Vesin
Sergen Cansiz
Yannick Bouillard
Irene Balelli
...
B. Houis
R. Modzelewski
O. Humbert
Melek Önen
Marco Lorenzi
FedML
OOD
108
11
0
24 Apr 2023
SLPerf: a Unified Framework for Benchmarking Split Learning
SLPerf: a Unified Framework for Benchmarking Split Learning
Tianchen Zhou
Zhanyi Hu
Bingzhe Wu
Cen Chen
FedML
27
4
0
04 Apr 2023
A Generalized Look at Federated Learning: Survey and Perspectives
A Generalized Look at Federated Learning: Survey and Perspectives
Taki Hasan Rafi
Faiza Anan Noor
Tahmid Hussain
Dong-Kyu Chae
Zhaohui Yang
OOD
FedML
42
0
0
26 Mar 2023
Exploring the Relevance of Data Privacy-Enhancing Technologies for AI
  Governance Use Cases
Exploring the Relevance of Data Privacy-Enhancing Technologies for AI Governance Use Cases
Emma Bluemke
Tantum Collins
Ben Garfinkel
Andrew Trask
22
10
0
15 Mar 2023
FedML Parrot: A Scalable Federated Learning System via
  Heterogeneity-aware Scheduling on Sequential and Hierarchical Training
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training
Zhenheng Tang
Xiaowen Chu
Ryan Yide Ran
Sunwoo Lee
S. Shi
Yonggang Zhang
Yuxin Wang
Alex Liang
A. Avestimehr
Chaoyang He
FedML
28
10
0
03 Mar 2023
Towards Automated Homomorphic Encryption Parameter Selection with Fuzzy
  Logic and Linear Programming
Towards Automated Homomorphic Encryption Parameter Selection with Fuzzy Logic and Linear Programming
José Cabrero-Holgueras
S. Pastrana
21
7
0
17 Feb 2023
XFL: A High Performace, Lightweighted Federated Learning Framework
XFL: A High Performace, Lightweighted Federated Learning Framework
Hong Wang
Yuanzhi Zhou
Chi Zhang
Chen Peng
Mingxia Huang
Yi Liu
Lintao Zhang
FedML
26
3
0
10 Feb 2023
Distributed Traffic Synthesis and Classification in Edge Networks: A
  Federated Self-supervised Learning Approach
Distributed Traffic Synthesis and Classification in Edge Networks: A Federated Self-supervised Learning Approach
Yong Xiao
Rong Xia
Yingyu Li
Guangming Shi
Diep N. Nguyen
D. Hoang
Dusit Niyato
Marwan Krunz
29
12
0
01 Feb 2023
Privacy and Efficiency of Communications in Federated Split Learning
Privacy and Efficiency of Communications in Federated Split Learning
Zongshun Zhang
Andrea Pinto
Valeria Turina
Flavio Esposito
I. Matta
FedML
38
32
0
04 Jan 2023
Modeling Global Distribution for Federated Learning with Label
  Distribution Skew
Modeling Global Distribution for Federated Learning with Label Distribution Skew
Tao Sheng
Cheng Shen
Yuan Liu
Yeyu Ou
Zhe Qu
Jianxin Wang
FedML
27
7
0
17 Dec 2022
Privacy-Preserving Collaborative Learning through Feature Extraction
Privacy-Preserving Collaborative Learning through Feature Extraction
A. Sarmadi
Hao Fu
Prashanth Krishnamurthy
S. Garg
Farshad Khorrami
FedML
32
6
0
13 Dec 2022
Private Multiparty Perception for Navigation
Private Multiparty Perception for Navigation
Hui Lu
Mia Chiquier
Carl Vondrick
EgoV
33
0
0
02 Dec 2022
Federated Learning for Healthcare Domain - Pipeline, Applications and
  Challenges
Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges
Madhura Joshi
Ankit Pal
Malaikannan Sankarasubbu
OOD
AI4CE
FedML
25
93
0
15 Nov 2022
TorchFL: A Performant Library for Bootstrapping Federated Learning
  Experiments
TorchFL: A Performant Library for Bootstrapping Federated Learning Experiments
Vivek Khimani
S. Jabbari
FedML
AI4CE
24
0
0
01 Nov 2022
Legal-Tech Open Diaries: Lesson learned on how to develop and deploy
  light-weight models in the era of humongous Language Models
Legal-Tech Open Diaries: Lesson learned on how to develop and deploy light-weight models in the era of humongous Language Models
Stelios Maroudas
Sotiris Legkas
Prodromos Malakasiotis
Ilias Chalkidis
VLM
AILaw
ALM
ELM
29
4
0
24 Oct 2022
Asynchronous Training Schemes in Distributed Learning with Time Delay
Asynchronous Training Schemes in Distributed Learning with Time Delay
Haoxiang Wang
Zhanhong Jiang
Chao Liu
S. Sarkar
D. Jiang
Young M. Lee
42
2
0
28 Aug 2022
Efficient ML Models for Practical Secure Inference
Efficient ML Models for Practical Secure Inference
Vinod Ganesan
Anwesh Bhattacharya
Pratyush Kumar
Divya Gupta
Rahul Sharma
Nishanth Chandran
MedIm
59
5
0
26 Aug 2022
Towards Energy-Aware Federated Learning on Battery-Powered Clients
Towards Energy-Aware Federated Learning on Battery-Powered Clients
Amna Arouj
A. Abdelmoniem
32
26
0
09 Aug 2022
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings
  through Graph Contrastive Learning
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning
Haoran Yang
Xiangyu Zhao
Muyang Li
Hongxu Chen
Guandong Xu
FedML
39
2
0
24 Jul 2022
Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive
  Privacy Analysis and Beyond
Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond
Yuzheng Hu
Tianle Cai
Jinyong Shan
Shange Tang
Chaochao Cai
Ethan Song
Bo-wen Li
D. Song
FedML
AAML
27
9
0
19 Jul 2022
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust
  Setting
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting
Runhua Xu
Nathalie Baracaldo
Yi Zhou
Ali Anwar
S. Kadhe
Heiko Ludwig
FedML
22
22
0
15 Jul 2022
Swan: A Neural Engine for Efficient DNN Training on Smartphone SoCs
Swan: A Neural Engine for Efficient DNN Training on Smartphone SoCs
Sanjay Sri Vallabh Singapuram
Fan Lai
Chuheng Hu
Mosharaf Chowdhury
32
5
0
09 Jun 2022
Test-Time Robust Personalization for Federated Learning
Test-Time Robust Personalization for Federated Learning
Liang Jiang
Tao R. Lin
FedML
OOD
TTA
85
43
0
22 May 2022
Secure Aggregation for Federated Learning in Flower
Secure Aggregation for Federated Learning in Flower
Kwing Hei Li
Pedro Porto Buarque de Gusmão
Daniel J. Beutel
Nicholas D. Lane
FedML
29
36
0
12 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
28
15
0
26 Apr 2022
Privacy-Preserving Aggregation in Federated Learning: A Survey
Privacy-Preserving Aggregation in Federated Learning: A Survey
Ziyao Liu
Jiale Guo
Wenzhuo Yang
Jiani Fan
Kwok-Yan Lam
Jun Zhao
FedML
37
87
0
31 Mar 2022
Towards Efficient and Stable K-Asynchronous Federated Learning with
  Unbounded Stale Gradients on Non-IID Data
Towards Efficient and Stable K-Asynchronous Federated Learning with Unbounded Stale Gradients on Non-IID Data
Zihao Zhou
Yanan Li
Xuebin Ren
Shusen Yang
28
29
0
02 Mar 2022
FL_PyTorch: optimization research simulator for federated learning
FL_PyTorch: optimization research simulator for federated learning
Konstantin Burlachenko
Samuel Horváth
Peter Richtárik
FedML
53
18
0
07 Feb 2022
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine
  Learning
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning
A. Mondal
Harpreet Virk
Debayan Gupta
45
15
0
06 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
31
6
0
03 Feb 2022
Recycling Model Updates in Federated Learning: Are Gradient Subspaces
  Low-Rank?
Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?
Sheikh Shams Azam
Seyyedali Hosseinalipour
Qiang Qiu
Christopher G. Brinton
FedML
31
20
0
01 Feb 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
27
11
0
19 Jan 2022
1234
Next