Adaptive Federated Optimization

29 February 2020

Sanjiv Kumar

Papers citing "Adaptive Federated Optimization"

42 / 792 papers shown

Title
Can Federated Learning Save The Planet? Xinchi Qiu Titouan Parcollet Daniel J. Beutel Taner Topal Akhil Mathur Nicholas D. Lane 23 79 0 13 Oct 2020
Oort: Efficient Federated Learning via Guided Participant Selection Fan Lai Xiangfeng Zhu H. Madhyastha Mosharaf Chowdhury FedML OODD 21 226 0 12 Oct 2020
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms Maruan Al-Shedivat Jennifer Gillenwater Eric Xing Afshin Rostamizadeh FedML 25 109 0 11 Oct 2020
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies Yae Jee Cho Jianyu Wang Gauri Joshi FedML 47 401 0 03 Oct 2020
FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling Cheng Chen Ziyi Chen Yi Zhou B. Kailkhura FedML 28 60 0 22 Sep 2020
Distilled One-Shot Federated Learning Yanlin Zhou George Pu Xiyao Ma Xiaolin Li D. Wu FedML DD 62 158 0 17 Sep 2020
Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data Qianqian Tong Guannan Liang J. Bi FedML 41 27 0 14 Sep 2020
FLaPS: Federated Learning and Privately Scaling Sudipta Paul Poushali Sengupta Subhankar Mishra FedML 19 4 0 13 Sep 2020
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning Hong-You Chen Wei-Lun Chao FedML 25 256 0 04 Sep 2020
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models Zhengming Zhang Yaoqing Yang Z. Yao Yujun Yan Joseph E. Gonzalez Michael W. Mahoney FedML 39 36 0 26 Aug 2020
Accelerating Federated Learning in Heterogeneous Data and Computational Environments Dimitris Stripelis J. Ambite FedML 20 11 0 25 Aug 2020
Adaptive Serverless Learning Hongchang Gao Heng-Chiao Huang 16 3 0 24 Aug 2020
FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching Farzin Haddadpour Belhal Karimi Ping Li Xiaoyun Li FedML 58 31 0 11 Aug 2020
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning Sai Praneeth Karimireddy Martin Jaggi Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 37 215 0 08 Aug 2020
Federated Transfer Learning with Dynamic Gradient Aggregation Dimitrios Dimitriadis K. Kumatani R. Gmyr Yashesh Gaur Sefik Emre Eskimez FedML 24 15 0 06 Aug 2020
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization Rui Hu Yanmin Gong Yuanxiong Guo FedML 26 54 0 01 Aug 2020
Communication-Efficient Federated Learning via Optimal Client Sampling Mónica Ribero H. Vikalo FedML 15 93 0 30 Jul 2020
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge Chaoyang He M. Annavaram A. Avestimehr FedML 21 23 0 28 Jul 2020
Flower: A Friendly Federated Learning Research Framework Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques ... Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 17 784 0 28 Jul 2020
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 168 564 0 27 Jul 2020
Fast-Convergent Federated Learning Hung T. Nguyen Vikash Sehwag Seyyedali Hosseinalipour Christopher G. Brinton M. Chiang H. Vincent Poor FedML 28 192 0 26 Jul 2020
Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing Jed Mills Jia Hu Geyong Min FedML 31 194 0 17 Jul 2020
Prioritized Multi-Criteria Federated Learning Vito Walter Anelli Yashar Deldjoo Tommaso Di Noia Antonio Ferrara FedML 11 9 0 17 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 16 1,297 0 15 Jul 2020
FedBoosting: Federated Learning with Gradient Protected Boosting for Text Recognition Hanchi Ren Jingjing Deng Xianghua Xie Xiaoke Ma Yi-Cheng Wang FedML 19 11 0 14 Jul 2020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees Farzin Haddadpour Mohammad Mahdi Kamani Aryan Mokhtari M. Mahdavi FedML 42 273 0 02 Jul 2020
On the Outsized Importance of Learning Rates in Local Update Methods Zachary B. Charles Jakub Konecný FedML 24 54 0 02 Jul 2020
Federated Learning Meets Multi-objective Optimization Zeou Hu K. Shaloudegi Guojun Zhang Yaoliang Yu FedML 23 89 0 20 Jun 2020
Personalized Federated Learning with Moreau Envelopes Canh T. Dinh N. H. Tran Tuan Dung Nguyen FedML 39 967 0 16 Jun 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning Tao R. Lin Lingjing Kong Sebastian U. Stich Martin Jaggi FedML 19 1,015 0 12 Jun 2020
STL-SGD: Speeding Up Local SGD with Stagewise Communication Period Shuheng Shen Yifei Cheng Jingchang Liu Linli Xu LRM 24 7 0 11 Jun 2020
Training Keyword Spotting Models on Non-IID Data with Federated Learning Andrew Straiton Hard Kurt Partridge Cameron Nguyen Niranjan A. Subrahmanya Aishanee Shah Pai Zhu Ignacio López Moreno Rajiv Mathews OOD FedML 8 63 0 21 May 2020
Pretraining Federated Text Models for Next Word Prediction Joel Stremmel Arjun Singh FedML 15 52 0 11 May 2020
Quantized Adam with Error Feedback Congliang Chen Li Shen Haozhi Huang Wei Liu ODL MQ 6 33 0 29 Apr 2020
Towards Federated Learning With Byzantine-Robust Client Weighting Amit Portnoy Yoav Tirosh Danny Hendler FedML 21 11 0 10 Apr 2020
Inverting Gradients -- How easy is it to break privacy in federated learning? Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 26 1,193 0 31 Mar 2020
Device Heterogeneity in Federated Learning: A Superquantile Approach Yassine Laguel Krishna Pillutla J. Malick Zaïd Harchaoui FedML 40 22 0 25 Feb 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 37 629 0 31 Dec 2019
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 74 6,091 0 10 Dec 2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection Yue Liu Zeyi Wen Zhaomin Wu Sixu Hu Naibo Wang Yuan N. Li Xu Liu Bingsheng He FedML 37 970 0 23 Jul 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 24 330 0 09 May 2019
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,687 0 14 Apr 2018