Papers citing "Advances and Open Problems in Federated Learning"

50 / 193 papers shown

Title
Byzantine-Resilient Secure Federated Learning Jinhyun So Başak Güler A. Avestimehr FedML 45 239 0 21 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 43 1,321 0 15 Jul 2020
Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy Nuria Rodríguez Barroso G. Stipcich Daniel Jiménez-López José Antonio Ruiz-Millán Eugenio Martínez-Cámara Gerardo González-Seco M. V. Luzón M. Veganzones Francisco Herrera 36 102 0 02 Jul 2020
On the Outsized Importance of Learning Rates in Local Update Methods Zachary B. Charles Jakub Konecný FedML 43 54 0 02 Jul 2020
Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup Seungeun Oh Jihong Park Eunjeong Jeong Hyesung Kim M. Bennis Seong-Lyun Kim FedML 49 58 0 17 Jun 2020
Understanding Unintended Memorization in Federated Learning Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Franccoise Beaufays FedML 35 47 0 12 Jun 2020
Privacy in Deep Learning: A Survey Fatemehsadat Mirshghallah Mohammadkazem Taram Praneeth Vepakomma Abhishek Singh Ramesh Raskar H. Esmaeilzadeh FedML 60 137 0 25 Apr 2020
Towards Non-I.I.D. and Invisible Data with FedNAS: Federated Deep Learning via Neural Architecture Search Chaoyang He M. Annavaram A. Avestimehr OOD FedML 42 87 0 18 Apr 2020
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation Chaoyang He Haishan Ye Li Shen Tong Zhang 49 129 0 27 Mar 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 243 1,045 0 06 Mar 2020
Decentralized gradient methods: does topology matter? Giovanni Neglia Chuan Xu Don Towsley G. Calbi 38 50 0 28 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 52 254 0 18 Feb 2020
Salvaging Federated Learning by Local Adaptation Tao Yu Eugene Bagdasaryan Vitaly Shmatikov FedML 41 262 0 12 Feb 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 71 644 0 31 Dec 2019
The power of synergy in differential privacy: Combining a small curator with local randomizers A. Beimel Aleksandra Korolova Kobbi Nissim Or Sheffet Uri Stemmer 50 14 0 18 Dec 2019
Can You Really Backdoor Federated Learning? Ziteng Sun Peter Kairouz A. Suresh H. B. McMahan FedML 58 565 0 18 Nov 2019
Secure Evaluation of Quantized Neural Networks Anders Dalskov Daniel E. Escudero Marcel Keller 54 138 0 28 Oct 2019
Federated Evaluation of On-device Personalization Kangkang Wang Rajiv Mathews Chloé Kiddon Hubert Eichner F. Beaufays Daniel Ramage FedML 43 283 0 22 Oct 2019
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Sai Praneeth Karimireddy Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 47 345 0 14 Oct 2019
The Non-IID Data Quagmire of Decentralized Machine Learning Kevin Hsieh Amar Phanishayee O. Mutlu Phillip B. Gibbons 119 563 0 01 Oct 2019
HEAX: An Architecture for Computing on Encrypted Data M. Riazi Kim Laine Blake Pelton Wei Dai 48 221 0 20 Sep 2019
Detailed comparison of communication efficiency of split learning and federated learning Abhishek Singh Praneeth Vepakomma O. Gupta Ramesh Raskar FedML 43 188 0 18 Sep 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 108 1,128 0 13 Sep 2019
On the Upload versus Download Cost for Secure and Private Matrix Multiplication Wei-Ting Chang Ravi Tandon FedML 32 42 0 25 Jun 2019
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model Badih Ghazi Rasmus Pagh A. Velingker FedML 37 98 0 19 Jun 2019
Federated Learning for Emoji Prediction in a Mobile Keyboard Swaroop Indra Ramaswamy Rajiv Mathews Kanishka Rao Franccoise Beaufays FedML 44 311 0 11 Jun 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi 56 320 0 31 May 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 78 474 0 28 May 2019
Decentralized Bayesian Learning over Graphs Anusha Lalitha Xinghan Wang O. Kilinc Y. Lu T. Javidi F. Koushanfar FedML 48 25 0 24 May 2019
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling Jianyu Wang Anit Kumar Sahu Zhouyi Yang Gauri Joshi S. Kar 48 162 0 23 May 2019
Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach Jiawen Kang Zehui Xiong Dusit Niyato Han Yu Ying-Chang Liang Dong In Kim FedML 47 213 0 16 May 2019
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression Hanlin Tang Xiangru Lian Chen Yu Tong Zhang Ji Liu 33 217 0 15 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 107 1,238 0 29 Apr 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 44 1,343 0 07 Mar 2019
Federated Heavy Hitters Discovery with Differential Privacy Wennan Zhu Peter Kairouz H. B. McMahan Haicheng Sun Wei Li FedML 52 108 0 22 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 62 211 0 21 Feb 2019
Federated Machine Learning: Concept and Applications Qiang Yang Yang Liu Tianjian Chen Yongxin Tong FedML 52 2,302 0 13 Feb 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 88 2,652 0 04 Feb 2019
Agnostic Federated Learning M. Mohri Gary Sivek A. Suresh FedML 88 928 0 01 Feb 2019
Peer-to-peer Federated Learning on Graphs Anusha Lalitha O. Kilinc T. Javidi F. Koushanfar OOD FedML 93 185 0 31 Jan 2019
SNAS: Stochastic Neural Architecture Search Sirui Xie Hehui Zheng Chunxiao Liu Liang Lin 59 932 0 24 Dec 2018
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 78 907 0 09 Dec 2018
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 104 1,410 0 03 Dec 2018
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 83 694 0 03 Dec 2018
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 167 423 0 29 Nov 2018
The Power of The Hybrid Model for Mean Estimation Brendan Avent Yatharth Dubey Aleksandra Korolova 65 16 0 29 Nov 2018
Stochastic Gradient Push for Distributed Deep Learning Mahmoud Assran Nicolas Loizou Nicolas Ballas Michael G. Rabbat 51 342 0 27 Nov 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 44 602 0 14 Oct 2018
Differentially Private Change-Point Detection Rachel Cummings Sara Krehbiel Y. Mei Rui Tuo Wanrong Zhang 18 30 0 29 Aug 2018
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms Jianyu Wang Gauri Joshi 101 348 0 22 Aug 2018