Distributed learning of deep neural network over multiple agents

14 October 2018

Papers citing "Distributed learning of deep neural network over multiple agents"

35 / 85 papers shown

Title
LSTMSPLIT: Effective SPLIT Learning based LSTM on Sequential Time-Series Data Lianlian Jiang Yuexuan Wang Wenyi Zheng Chao Jin Zengxiang Li Sin Gee Teo AI4TS 33 10 0 08 Mar 2022
Differentially Private Label Protection in Split Learning Xin Yang Jiankai Sun Yuanshun Yao Junyuan Xie Chong-Jun Wang FedML 44 36 0 04 Mar 2022
Label Leakage and Protection from Forward Embedding in Vertical Federated Learning Jiankai Sun Xin Yang Yuanshun Yao Chong-Jun Wang FedML 36 37 0 02 Mar 2022
Learning-Driven Lossy Image Compression; A Comprehensive Survey Sonain Jamil Md. Jalil Piran Muhibur Rahman 34 36 0 23 Jan 2022
Long-term Data Sharing under Exclusivity Attacks Yotam gafni Moshe Tennenholtz 22 2 0 22 Jan 2022
Feature Space Hijacking Attacks against Differentially Private Split Learning Grzegorz Gawron P. Stubbings AAML 27 20 0 11 Jan 2022
FLoBC: A Decentralized Blockchain-Based Federated Learning Framework M. C. Ghanem Fadi Dawoud Habiba Gamal E. Soliman Hossam Sharara Tamer El-Batt 21 10 0 22 Dec 2021
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications Khaled B. Letaief Yuanming Shi Jianmin Lu Jianhua Lu 43 417 0 24 Nov 2021
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning Yuezhou Wu Yan Kang Jiahuan Luo Yuanqin He Qiang Yang FedML AAML 19 69 0 16 Nov 2021
SplitGuard: Detecting and Mitigating Training-Hijacking Attacks in Split Learning Ege Erdogan Alptekin Kupcu A. E. Cicek AAML 22 32 0 20 Aug 2021
UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning Ege Erdogan Alptekin Kupcu A. E. Cicek FedML MIACV 35 77 0 20 Aug 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
Towards Representation Identical Privacy-Preserving Graph Neural Network via Split Learning Chuanqiang Shan Hui Jiao Jie Fu 21 14 0 13 Jul 2021
In-Network Learning: Distributed Training and Inference in Networks Matei Moldoveanu Milad Sefidgaran 27 11 0 07 Jul 2021
Vertical Federated Learning without Revealing Intersection Membership Jiankai Sun Xin Yang Yuanshun Yao Aonan Zhang Weihao Gao Junyuan Xie Chong-Jun Wang FedML 31 37 0 10 Jun 2021
Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX Chengliang Zhang Junzhe Xia Baichen Yang Huancheng Puyang Wei Wang Ruichuan Chen Istemi Ekin Akkus Paarijaat Aditya Feng Yan FedML 53 39 0 04 May 2021
On In-network learning. A Comparative Study with Federated and Split Learning Matei Moldoveanu Milad Sefidgaran FedML 24 7 0 30 Apr 2021
PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN Daniele Romanini A. Hall Pavlos Papadopoulos Tom Titcombe Abbas Ismail Tudor Cebere R. Sandmann Robin Roehm Michael A. Hoeh FedML MU 15 91 0 01 Apr 2021
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of Things Yansong Gao Minki Kim Chandra Thapa Sharif Abuadbba Zhi-Li Zhang S. Çamtepe Hyoungshick Kim Surya Nepal 30 59 0 03 Mar 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 209 841 0 01 Mar 2021
Unleashing the Tiger: Inference Attacks on Split Learning Dario Pasquini G. Ateniese M. Bernaschi FedML 34 147 0 04 Dec 2020
Advancements of federated learning towards privacy preservation: from federated learning to split learning Chandra Thapa Pathum Chamikara Mahawaga Arachchige S. Çamtepe FedML 22 82 0 25 Nov 2020
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning Nick Angelou Ayoub Benaissa Bogdan Cebere William Clark A. Hall ... Pavlos Papadopoulos Robin Roehm R. Sandmann Phillipp Schoppmann Tom Titcombe 19 27 0 18 Nov 2020
SplitEasy: A Practical Approach for Training ML models on Mobile Devices Kamalesh Palanisamy Vivek Khimani Moin Hussain Moti Dimitris Chatzopoulos 22 20 0 09 Nov 2020
ASFGNN: Automated Separated-Federated Graph Neural Network Longfei Zheng Jun Zhou Chaochao Chen Bingzhe Wu L. xilinx Wang Benyu Zhang FedML GNN 28 71 0 06 Nov 2020
FedSL: Federated Split Learning on Distributed Sequential Data in Recurrent Neural Networks Ali Abedi Shehroz S. Khan FedML 39 53 0 06 Nov 2020
NoPeek: Information leakage reduction to share activations in distributed deep learning Praneeth Vepakomma Abhishek Singh O. Gupta Ramesh Raskar MIACV FedML 24 84 0 20 Aug 2020
SplitNN-driven Vertical Partitioning Iker Ceballos Vivek Sharma Eduardo Mugica Abhishek Singh Alberto Roman Praneeth Vepakomma Ramesh Raskar 26 72 0 07 Aug 2020
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems Sixu Hu Yuan N. Li Xu Liu Yue Liu Zhaomin Wu Bingsheng He FedML 18 53 0 14 Jun 2020
Contention Window Optimization in IEEE 802.11ax Networks with Deep Reinforcement Learning Witold Wydmański S. Szott 21 48 0 03 Mar 2020
Communication-Efficient Edge AI: Algorithms and Systems Yuanming Shi Kai Yang Tao Jiang Jun Zhang Khaled B. Letaief GNN 29 326 0 22 Feb 2020
Split Learning for collaborative deep learning in healthcare M. Poirot Praneeth Vepakomma Ken Chang Jayashree Kalpathy-Cramer Rajiv Gupta Ramesh Raskar FedML OOD 34 135 0 27 Dec 2019
Federated and Differentially Private Learning for Electronic Health Records Stephen R. Pfohl Andrew M. Dai Katherine A. Heller OOD FedML 23 49 0 13 Nov 2019
No Peek: A Survey of private distributed deep learning Praneeth Vepakomma Tristan Swedish Ramesh Raskar O. Gupta Abhimanyu Dubey SyDa FedML 30 99 0 08 Dec 2018
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 63 692 0 03 Dec 2018