Papers citing "Advances and Open Problems in Federated Learning"

50 / 757 papers shown

Title
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 21 636 0 16 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 14 1,295 0 15 Jul 2020
Differentially private cross-silo federated learning Mikko A. Heikkilä A. Koskela Kana Shimizu Samuel Kaski Antti Honkela FedML 13 24 0 10 Jul 2020
Federated Learning Meets Multi-objective Optimization Zeou Hu K. Shaloudegi Guojun Zhang Yaoliang Yu FedML 8 89 0 20 Jun 2020
FedCD: Improving Performance in non-IID Federated Learning Kavya Kopparapu Eric Lin Jessica Zhao FedML 13 35 0 17 Jun 2020
Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh Farzan Farnia Ramtin Pedarsani Ali Jadbabaie FedML OOD 30 161 0 16 Jun 2020
Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention Ce Ju Ruihui Zhao Jichao Sun Xiguang Wei Bo Zhao ... Dashan Gao Ben Tan Han Yu Chuning He Yuan Jin FedML OOD 6 33 0 15 Jun 2020
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems Sixu Hu Yuan N. Li Xu Liu Q. Li Zhaomin Wu Bingsheng He FedML 11 53 0 14 Jun 2020
Privacy-Preserving Image Features via Adversarial Affine Subspace Embeddings Mihai Dusmanu Johannes L. Schonberger Sudipta N. Sinha Marc Pollefeys PICV 28 9 0 11 Jun 2020
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies Yu Huang Yue Chen 3DPC 29 81 0 10 Jun 2020
XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning Myungjae Shin Chihoon Hwang Joongheon Kim Jihong Park M. Bennis Seong-Lyun Kim FedML 17 108 0 09 Jun 2020
Secure Byzantine-Robust Machine Learning Lie He Sai Praneeth Karimireddy Martin Jaggi OOD 18 58 0 08 Jun 2020
Minibatch vs Local SGD for Heterogeneous Distributed Learning Blake E. Woodworth Kumar Kshitij Patel Nathan Srebro FedML 22 198 0 08 Jun 2020
FedSplit: An algorithmic framework for fast federated optimization Reese Pathak Martin J. Wainwright FedML 29 182 0 11 May 2020
CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning Yuanrui Dong Peng Zhao Hanqiao Yu Cong Zhao Shusen Yang 15 19 0 04 May 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 52 49 0 01 Apr 2020
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 186 542 0 30 Mar 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova Nicolas Loizou Sadra Boreiri Martin Jaggi Sebastian U. Stich FedML 37 491 0 23 Mar 2020
Resilience in Collaborative Optimization: Redundant and Independent Cost Functions Nirupam Gupta Nitin H. Vaidya 9 18 0 21 Mar 2020
Federated Continual Learning with Weighted Inter-client Transfer Jaehong Yoon Wonyoung Jeong Giwoong Lee Eunho Yang Sung Ju Hwang FedML 21 199 0 06 Mar 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 178 1,027 0 06 Mar 2020
User-Level Privacy-Preserving Federated Learning: Analysis and Performance Optimization Kang Wei Jun Li Ming Ding Chuan Ma Hang Su Bo-Wen Zhang H. Vincent Poor FedML 17 11 0 29 Feb 2020
Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees Richeng Jin Yufan Huang Xiaofan He H. Dai Tianfu Wu FedML 22 63 0 25 Feb 2020
Three Approaches for Personalization with Applications to Federated Learning Yishay Mansour M. Mohri Jae Hun Ro A. Suresh FedML 34 565 0 25 Feb 2020
Personalized Federated Learning: A Meta-Learning Approach Alireza Fallah Aryan Mokhtari Asuman Ozdaglar FedML 11 560 0 19 Feb 2020
Is Local SGD Better than Minibatch SGD? Blake E. Woodworth Kumar Kshitij Patel Sebastian U. Stich Zhen Dai Brian Bullins H. B. McMahan Ohad Shamir Nathan Srebro FedML 34 253 0 18 Feb 2020
Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability Yikai Yan Chaoyue Niu Yucheng Ding Zhenzhe Zheng Fan Wu Guihai Chen Shaojie Tang Zhihua Wu FedML 28 37 0 18 Feb 2020
Federated Learning with Matched Averaging Hongyi Wang Mikhail Yurochkin Yuekai Sun Dimitris Papailiopoulos Y. Khazaeni FedML 14 1,096 0 15 Feb 2020
Faster On-Device Training Using New Federated Momentum Algorithm Zhouyuan Huo Qian Yang Bin Gu Heng-Chiao Huang FedML 4 47 0 06 Feb 2020
Pure Differentially Private Summation from Anonymous Messages Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Rasmus Pagh A. Velingker FedML 15 46 0 05 Feb 2020
Learning to Detect Malicious Clients for Robust Federated Learning Suyi Li Yong Cheng Wei Wang Yang Liu Tianjian Chen AAML FedML 8 223 0 01 Feb 2020
Multi-Participant Multi-Class Vertical Federated Learning Siwei Feng Han Yu FedML 14 88 0 30 Jan 2020
Stratified cross-validation for unbiased and privacy-preserving federated learning R. Bey Romain Goussault M. Benchoufi R. Porcher FedML 14 12 0 22 Jan 2020
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach Pengchao Han Shiqiang Wang K. Leung FedML 22 175 0 14 Jan 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 30 627 0 31 Dec 2019
Variance Reduced Local SGD with Lower Communication Complexity Xian-Feng Liang Shuheng Shen Jingchang Liu Zhen Pan Enhong Chen Yifei Cheng FedML 14 152 0 30 Dec 2019
Improved Differentially Private Decentralized Source Separation for fMRI Data H. Imtiaz Jafar Mohammadi Rogers F. Silva Bradley T. Baker Sergey Plis Anand D. Sarwate Vince D. Calhoun OOD 11 5 0 28 Oct 2019
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning Anis Elgabli Jihong Park Amrit Singh Bedi Chaouki Ben Issaid M. Bennis Vaneet Aggarwal 11 66 0 23 Oct 2019
The Non-IID Data Quagmire of Decentralized Machine Learning Kevin Hsieh Amar Phanishayee O. Mutlu Phillip B. Gibbons 6 555 0 01 Oct 2019
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 157 760 0 28 Sep 2019
Model Pruning Enables Efficient Federated Learning on Edge Devices Yuang Jiang Shiqiang Wang Victor Valls Bongjun Ko Wei-Han Lee Kin K. Leung Leandros Tassiulas 22 443 0 26 Sep 2019
Improved Summation from Shuffling Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 48 22 0 24 Sep 2019
Private Aggregation from Fewer Anonymous Messages Badih Ghazi Pasin Manurangsi Rasmus Pagh A. Velingker FedML 37 55 0 24 Sep 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 19 121 0 04 Jun 2019
SecureBoost: A Lossless Federated Learning Framework Kewei Cheng Tao Fan Yilun Jin Yang Liu Tianjian Chen Dimitrios Papadopoulos Qiang Yang FedML 8 578 0 25 Jan 2019
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 168 287 0 02 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 177 1,032 0 29 Nov 2018
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 136 420 0 29 Nov 2018
Don't Use Large Mini-Batches, Use Local SGD Tao R. Lin Sebastian U. Stich Kumar Kshitij Patel Martin Jaggi 14 429 0 22 Aug 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 112 395 0 08 Jun 2018