Split learning for health: Distributed deep learning without sharing raw patient data

3 December 2018

Papers citing "Split learning for health: Distributed deep learning without sharing raw patient data"

50 / 343 papers shown

Title
Passive Inference Attacks on Split Learning via Adversarial Regularization Xiaochen Zhu Xinjian Luo Yuncheng Wu Yangfan Jiang Xiaokui Xiao Beng Chin Ooi FedML 24 9 0 16 Oct 2023
Semantics Alignment via Split Learning for Resilient Multi-User Semantic Communication Jinhyuk Choi Jihong Park Seung-Woo Ko Jinho D. Choi M. Bennis Seong-Lyun Kim 38 3 0 13 Oct 2023
Split-and-Denoise: Protect large language model inference with local differential privacy Peihua Mai Ran Yan Zhe Huang Youjia Yang Yan Pang 27 10 0 13 Oct 2023
Collaborative Distributed Machine Learning Sumit Kumar Jha Patrick Lincoln Sascha Rank A. Sunyaev 30 1 0 28 Sep 2023
Love or Hate? Share or Split? Privacy-Preserving Training Using Split Learning and Homomorphic Encryption Tanveer Khan Khoa Nguyen A. Michalas Alexandros Bakas FedML 11 12 0 19 Sep 2023
A More Secure Split: Enhancing the Security of Privacy-Preserving Split Learning Tanveer Khan Khoa Nguyen A. Michalas 11 9 0 15 Sep 2023
Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference Kiwan Maeng G. E. Suh 30 2 0 09 Sep 2023
Split Without a Leak: Reducing Privacy Leakage in Split Learning Khoa Nguyen Tanveer Khan A. Michalas FedML 16 4 0 30 Aug 2023
Federated Learning for Computer Vision Yassine Himeur Iraklis Varlamis Hamza Kheddar Abbes Amira Shadi Atalla Yashbir Singh F. Bensaali W. Mansoor FedML 26 20 0 24 Aug 2023
When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation Chao Huang Geng Tian Ming Tang FedML 34 4 0 23 Aug 2023
Split Learning for Distributed Collaborative Training of Deep Learning Models in Health Informatics Zhuohang Li Chao Yan Xinmeng Zhang Gharib Gharibi Zhijun Yin Xiaoqian Jiang B. Malin FedML 19 10 0 21 Aug 2023
GradientCoin: A Peer-to-Peer Decentralized Large Language Models Yeqi Gao Zhao-quan Song Junze Yin 23 18 0 21 Aug 2023
Split Unlearning Guangsheng Yu Xu Wang Caijun Sun Xu Wang Baihe Ma Caijun Sun Wei Ni Ren Ping Liu MU 11 0 0 21 Aug 2023
FedSIS: Federated Split Learning with Intermediate Representation Sampling for Privacy-preserving Generalized Face Presentation Attack Detection Naif Alkhunaizi K. Srivatsan Faris Almalik Ibrahim Almakky Karthik Nandakumar FedML 43 1 0 20 Aug 2023
Defending Label Inference Attacks in Split Learning under Regression Setting Haoze Qiu Fei Zheng Chaochao Chen Xiaolin Zheng FedML AAML 28 2 0 18 Aug 2023
Optimal Resource Allocation for U-Shaped Parallel Split Learning Song Lyu Zhengyi Lin Guanqiao Qu Xianhao Chen Xiaoxia Huang P. Li 25 27 0 17 Aug 2023
When Federated Learning meets Watermarking: A Comprehensive Overview of Techniques for Intellectual Property Protection Mohammed Lansari R. Bellafqira K. Kapusta V. Thouvenot Olivier Bettan G. Coatrieux FedML 28 15 0 07 Aug 2023
On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook Mingyuan Fan Chengyu Wang Cen Chen Yang Liu Jun Huang HILM 33 3 0 31 Jul 2023
SplitFed resilience to packet loss: Where to split, that is the question C. Shiranthika Zahra Hafezi Kafshgari Parvaneh Saeedi Ivan V. Bajić 30 2 0 25 Jul 2023
Training Latency Minimization for Model-Splitting Allowed Federated Edge Learning Yao Wen GuoPeng Zhang Kezhi Wang Kun Yang FedML 30 3 0 21 Jul 2023
Communication-Efficient Split Learning via Adaptive Feature-Wise Compression Yong-Nam Oh Jaeho Lee Christopher G. Brinton Yo-Seb Jeon MQ 33 7 0 20 Jul 2023
On the Robustness of Split Learning against Adversarial Attacks Mingyuan Fan Cen Chen Chengyu Wang Wenmeng Zhou Jun Huang AAML 20 8 0 16 Jul 2023
Towards Open Federated Learning Platforms: Survey and Vision from Technical and Legal Perspectives Moming Duan Qinbin Li Linshan Jiang Bingsheng He FedML 34 4 0 05 Jul 2023
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks Zhaomin Wu Junyi Hou Bin He FedML 54 5 0 05 Jul 2023
Analyzing the vulnerabilities in SplitFed Learning: Assessing the robustness against Data Poisoning Attacks Aysha Thahsin Zahir Ismail R. Shukla AAML FedML 29 6 0 04 Jul 2023
Secure and Fast Asynchronous Vertical Federated Learning via Cascaded Hybrid Optimization Ganyu Wang Qingsong Zhang Li Xiang Boyu Wang Bin Gu Charles X. Ling FedML 29 2 0 28 Jun 2023
FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling Faris Almalik Naif Alkhunaizi Ibrahim Almakky Karthik Nandakumar FedML MedIm 22 9 0 26 Jun 2023
Split Learning in 6G Edge Networks Zhengyi Lin Guanqiao Qu Xianhao Chen Kaibin Huang 24 70 0 21 Jun 2023
Leveraging The Edge-to-Cloud Continuum for Scalable Machine Learning on Decentralized Data A. Abdelmoniem 39 1 0 19 Jun 2023
Unraveling the Interconnected Axes of Heterogeneity in Machine Learning for Democratic and Inclusive Advancements Maryam Molamohammadi Afaf Taik Nicolas Le Roux G. Farnadi 29 1 0 11 Jun 2023
Improving Accelerated Federated Learning with Compression and Importance Sampling Michal Grudzieñ Grigory Malinovsky Peter Richtárik FedML 35 8 0 05 Jun 2023
Reducing Communication for Split Learning by Randomized Top-k Sparsification Fei Zheng Chaochao Chen Lingjuan Lyu Binhui Yao FedML 26 10 0 29 May 2023
When Computing Power Network Meets Distributed Machine Learning: An Efficient Federated Split Learning Framework Xinjing Yuan Lingjun Pu Lei Jiao Xiaofei Wang Mei Yang Jingdong Xu FedML 27 4 0 22 May 2023
FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning Penghui Wei Hongjian Dou Shaoguo Liu Rong Tang Li Liu Liangji Wang Bo Zheng FedML 24 12 0 15 May 2023
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information Kiwan Maeng Chuan Guo Sanjay Kariyappa G. E. Suh 16 8 0 06 May 2023
HTPS: Heterogeneous Transferring Prediction System for Healthcare Datasets Jia-Hao Syu Chun-Wei Lin M. Fojcik Rafał Cupek 11 2 0 02 May 2023
Quality-Adaptive Split-Federated Learning for Segmenting Medical Images with Inaccurate Annotations Zahra Hafezi Kafshgari C. Shiranthika Parvaneh Saeedi Ivan V. Bajić FedML 11 6 0 28 Apr 2023
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models Songze Li Duanyi Yao Jin Liu FedML 30 28 0 26 Apr 2023
Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities Xianhao Chen Yiqin Deng Haichuan Ding Guanqiao Qu Haixia Zhang P. Li Yuguang Fang GNN 37 40 0 22 Apr 2023
BadVFL: Backdoor Attacks in Vertical Federated Learning Mohammad Naseri Yufei Han Emiliano De Cristofaro FedML AAML 24 11 0 18 Apr 2023
EcoFed: Efficient Communication for DNN Partitioning-based Federated Learning Di Wu R. Ullah Philip Rodgers Peter Kilpatrick I. Spence Blesson Varghese FedML 27 1 0 11 Apr 2023
A Survey on Vertical Federated Learning: From a Layered Perspective Liu Yang Di Chai Junxue Zhang Yilun Jin Leye Wang Hao Liu Han Tian Qian Xu Kai Chen FedML 32 28 0 04 Apr 2023
SLPerf: a Unified Framework for Benchmarking Split Learning Tianchen Zhou Zhanyi Hu Bingzhe Wu Cen Chen FedML 17 4 0 04 Apr 2023
FedIN: Federated Intermediate Layers Learning for Model Heterogeneity Yun-Hin Chan Zhihan Jiang Jing Deng Edith C. H. Ngai FedML 24 1 0 03 Apr 2023
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples Jingwei Sun Ziyue Xu Dong Yang V. Nath Wenqi Li Can Zhao Daguang Xu Yiran Chen H. Roth FedML 32 14 0 28 Mar 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 36 0 0 26 Mar 2023
Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks Zhengyi Lin Guangyu Zhu Yiqin Deng Xianhao Chen Yue Gao Kaibin Huang Yuguang Fang 26 101 0 26 Mar 2023
Federated Learning without Full Labels: A Survey Yilun Jin Yang Liu Kai Chen Qian Yang FedML 12 26 0 25 Mar 2023
PFSL: Personalized & Fair Split Learning with Data & Label Privacy for thin clients Manas Wadhwa Gagan Raj Gupta Ashutosh Sahu Rahul Saini Vidhi Mittal FedML 19 6 0 19 Mar 2023
Applications of Federated Learning in Manufacturing: Identifying the Challenges and Exploring the Future Directions with Industry 4.0 and 5.0 Visions Farzana Islam Ahmed Shoyeb Raihan Imtiaz Ahmed FedML AI4CE 11 4 0 27 Feb 2023