A generic framework for privacy preserving deep learning

9 November 2018

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 Alexandre Cotorobai Jorge Miguel Silva Jose Luis Oliveira OOD FedML 37 0 0 12 May 2025
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 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 Ming Li Pengcheng Xu Junjie Hu Zeyu Tang Guang Yang FedML 50 1 0 15 Sep 2024
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 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 René Schwermer R. Mayer Hans-Arno Jacobsen FedML 43 1 0 03 Apr 2024
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 Mojtaba Ahmadi Reza Nourmohammadi 27 7 0 01 Dec 2023
Edge AI for Internet of Energy: Challenges and Perspectives Yassine Himeur A. Sayed A. Alsalemi F. Bensaali Abbes Amira 59 26 0 28 Nov 2023
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 Jorge Castillo Phillip Rieger Hossein Fereidooni Qian Chen Ahmad Sadeghi FedML AAML 43 8 0 03 Oct 2023
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 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 Ziyi 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 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 Harshit Daga Jae-Kwang Shin D. Garg Ada Gavrilovska Myungjin Lee Ramana Rao Kompella AI4CE 39 10 0 09 May 2023
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 Francesco Cremonesi Marc Vesin Sergen Cansiz Yannick Bouillard Irene Balelli ... B. Houis R. Modzelewski O. Humbert Melek Önen Marco Lorenzi FedML OOD 111 11 0 24 Apr 2023
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 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 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 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 José Cabrero-Holgueras S. Pastrana 21 7 0 17 Feb 2023
XFL: A High Performace, Lightweighted Federated Learning Framework Hong Wang Yuanzhi Zhou Chi Zhang Chen Peng Mingxia Huang Yi Liu Lintao Zhang FedML 28 3 0 10 Feb 2023
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 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 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 A. Sarmadi Hao Fu Prashanth Krishnamurthy S. Garg Farshad Khorrami FedML 32 6 0 13 Dec 2022
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 Madhura Joshi Ankit Pal Malaikannan Sankarasubbu OOD AI4CE FedML 25 93 0 15 Nov 2022
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 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 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 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 Amna Arouj A. Abdelmoniem 32 26 0 09 Aug 2022
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 Yuzheng Hu Tianle Cai Jinyong Shan Shange Tang Chaochao Cai Ethan Song Bo-wen Li D. Song FedML AAML 30 9 0 19 Jul 2022
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting Runhua Xu Nathalie Baracaldo Yi Zhou Ali Anwar S. Kadhe Heiko Ludwig FedML 38 22 0 15 Jul 2022
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 Liang Jiang Tao R. Lin FedML OOD TTA 85 43 0 22 May 2022
Secure Aggregation for Federated Learning in Flower Kwing Hei Li Pedro Porto Buarque de Gusmão Daniel J. Beutel Nicholas D. Lane FedML 37 36 0 12 May 2022
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 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 Zihao Zhou Yanan Li Xuebin Ren Shusen Yang 28 29 0 02 Mar 2022
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 A. Mondal Harpreet Virk Debayan Gupta 45 15 0 06 Feb 2022
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? Sheikh Shams Azam Seyyedali Hosseinalipour Qiang Qiu Christopher G. Brinton FedML 33 20 0 01 Feb 2022
SCOTCH: An Efficient Secure Computation Framework for Secure Aggregation Yash More Prashanthi Ramachandran Priyam Panda A. Mondal Harpreet Virk Debayan Gupta FedML 29 11 0 19 Jan 2022