Papers citing "A Field Guide to Federated Optimization"

50 / 108 papers shown

Title
Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction Xianghang Liu Bartlomiej Twardowski Tri Kurniawan Wijaya FedML 21 1 0 30 Aug 2022
Accelerating Vertical Federated Learning Dongqi Cai Tao Fan Yan Kang Lixin Fan Mengwei Xu Shangguang Wang Qiang Yang FedML 16 7 0 23 Jul 2022
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation Sungwon Han Sungwon Park Fangzhao Wu Sundong Kim Chuhan Wu Xing Xie M. Cha FedML 24 53 0 19 Jul 2022
Multi-Level Branched Regularization for Federated Learning Jinkyu Kim Geeho Kim Bohyung Han FedML 10 53 0 14 Jul 2022
One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis Onat Dalmaz Muhammad Usama Mirza Gokberk Elmas Muzaffer Özbey S. Dar Emir Ceyani Salman Avestimehr Tolga cCukur MedIm 25 39 0 13 Jul 2022
Towards the Practical Utility of Federated Learning in the Medical Domain Seongjun Yang Hyeonji Hwang Daeyoung Kim Radhika Dua Jong-Yeup Kim Eunho Yang E. Choi FedML OOD 16 15 0 07 Jul 2022
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning John Nguyen Jianyu Wang Kshitiz Malik Maziar Sanjabi Michael G. Rabbat FedML AI4CE 23 21 0 30 Jun 2022
FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization Zhen Wang Weirui Kuang Ce Zhang Bolin Ding Yaliang Li FedML 18 13 0 08 Jun 2022
Gradient Obfuscation Gives a False Sense of Security in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 28 46 0 08 Jun 2022
Certified Robustness in Federated Learning Motasem Alfarra Juan C. Pérez Egor Shulgin Peter Richtárik Bernard Ghanem AAML FedML 18 7 0 06 Jun 2022
On the Generalization of Wasserstein Robust Federated Learning Tung Nguyen Tuan Dung Nguyen Long Tan Le Canh T. Dinh N. H. Tran OOD FedML 21 6 0 03 Jun 2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity Kiwan Maeng Haiyu Lu Luca Melis John Nguyen Michael G. Rabbat Carole-Jean Wu FedML 29 31 0 30 May 2022
DELTA: Diverse Client Sampling for Fasting Federated Learning Lung-Chuang Wang Yongxin Guo Tao R. Lin Xiaoying Tang FedML 23 21 0 27 May 2022
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation Ljubomir Rokvic Panayiotis Danassis Sai Praneeth Karimireddy Boi Faltings TDI 25 1 0 23 May 2022
Federated Progressive Sparsification (Purge, Merge, Tune)+ Dimitris Stripelis Umang Gupta Greg Ver Steeg J. Ambite FedML 15 9 0 26 Apr 2022
Federated Learning with Partial Model Personalization Krishna Pillutla Kshitiz Malik Abdel-rahman Mohamed Michael G. Rabbat Maziar Sanjabi Lin Xiao FedML 39 154 0 08 Apr 2022
Over-the-Air Federated Learning via Second-Order Optimization Peng Yang Yuning Jiang Ting Wang Yong Zhou Yuanming Shi Colin N. Jones 40 28 0 29 Mar 2022
Federated Named Entity Recognition Joel Mathew Dimitris Stripelis J. Ambite FedML 20 1 0 28 Mar 2022
SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks Won Joon Yun Yunseok Kwak Hankyul Baek Soyi Jung Mingyue Ji M. Bennis Jihong Park Joongheon Kim 13 16 0 26 Mar 2022
Adaptive Aggregation For Federated Learning K. R. Jayaram Vinod Muthusamy Gegi Thomas Ashish Verma Mark Purcell FedML 25 16 0 23 Mar 2022
Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning Lin Zhang Li Shen Liang Ding Dacheng Tao Ling-Yu Duan FedML 28 252 0 17 Mar 2022
On the Convergence of Clustered Federated Learning Ma Jie Guodong Long Tianyi Zhou Jing Jiang Chengqi Zhang FedML 33 46 0 13 Feb 2022
Private Adaptive Optimization with Side Information Tian Li Manzil Zaheer Sashank J. Reddi Virginia Smith 24 35 0 12 Feb 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning A. Bietti Chen-Yu Wei Miroslav Dudík John Langford Zhiwei Steven Wu FedML 20 43 0 10 Feb 2022
Federated Learning Challenges and Opportunities: An Outlook Jie Ding Eric W. Tramel Anit Kumar Sahu Shuang Wu Salman Avestimehr Tao Zhang FedML 33 55 0 01 Feb 2022
Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning Wenzhi Fang Ziyi Yu Yuning Jiang Yuanming Shi Colin N. Jones Yong Zhou FedML 76 56 0 24 Jan 2022
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks Hankyul Baek Won Joon Yun Yunseok Kwak Soyi Jung Mingyue Ji M. Bennis Jihong Park Joongheon Kim FedML 66 21 0 05 Dec 2021
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications Khaled B. Letaief Yuanming Shi Jianmin Lu Jianhua Lu 34 416 0 24 Nov 2021
Linear Speedup in Personalized Collaborative Learning El Mahdi Chayti Sai Praneeth Karimireddy Sebastian U. Stich Nicolas Flammarion Martin Jaggi FedML 15 13 0 10 Nov 2021
Towards Model Agnostic Federated Learning Using Knowledge Distillation A. Afonin Sai Praneeth Karimireddy FedML 30 44 0 28 Oct 2021
What Do We Mean by Generalization in Federated Learning? Honglin Yuan Warren Morningstar Lin Ning K. Singhal OOD FedML 24 71 0 27 Oct 2021
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models Liam H. Fowl Jonas Geiping W. Czaja Micah Goldblum Tom Goldstein FedML 15 144 0 25 Oct 2021
Partial Variable Training for Efficient On-Device Federated Learning Tien-Ju Yang Dhruv Guliani F. Beaufays Giovanni Motta FedML 19 25 0 11 Oct 2021
Enabling On-Device Training of Speech Recognition Models with Federated Dropout Dhruv Guliani Lillian Zhou Changwan Ryu Tien-Ju Yang Harry Zhang Yong Xiao F. Beaufays Giovanni Motta FedML 17 16 0 07 Oct 2021
FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective Huan Zhang Mi Zhang Xin Liu P. Mohapatra Michael DeLucia FedML 23 18 0 06 Oct 2021
Efficient and Private Federated Learning with Partially Trainable Networks Hakim Sidahmed Zheng Xu Ankush Garg Yuan Cao Mingqing Chen FedML 49 13 0 06 Oct 2021
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision Chaoyang He Zhengyu Yang Erum Mushtaq Sunwoo Lee Mahdi Soltanolkotabi A. Avestimehr FedML 98 36 0 06 Oct 2021
FairFed: Enabling Group Fairness in Federated Learning Yahya H. Ezzeldin Shen Yan Chaoyang He Emilio Ferrara A. Avestimehr FedML 28 197 0 02 Oct 2021
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis Fatemehsadat Mireshghallah Vaishnavi Shrivastava Milad Shokouhi Taylor Berg-Kirkpatrick Robert Sim Dimitrios Dimitriadis FedML 40 33 0 01 Oct 2021
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer Yae Jee Cho Jianyu Wang Tarun Chiruvolu Gauri Joshi FedML 32 30 0 16 Sep 2021
Scalable Average Consensus with Compressed Communications Taha Toghani César A. Uribe 17 7 0 14 Sep 2021
Iterated Vector Fields and Conservatism, with Applications to Federated Learning Zachary B. Charles Keith Rush 24 6 0 08 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 49 515 0 31 Aug 2021
Federated Learning with Buffered Asynchronous Aggregation John Nguyen Kshitiz Malik Hongyuan Zhan Ashkan Yousefpour Michael G. Rabbat Mani Malek Dzmitry Huba FedML 21 288 0 11 Jun 2021
From Distributed Machine Learning to Federated Learning: A Survey Ji Liu Jizhou Huang Yang Zhou Xuhong Li Shilei Ji Haoyi Xiong Dejing Dou FedML OOD 44 243 0 29 Apr 2021
FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning Minxue Tang Xuefei Ning Yitu Wang Jingwei Sun Yu Wang H. Li Yiran Chen FedML 19 79 0 24 Mar 2021
Practical and Private (Deep) Learning without Sampling or Shuffling Peter Kairouz Brendan McMahan Shuang Song Om Thakkar Abhradeep Thakurta Zheng Xu FedML 182 154 0 26 Feb 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 178 267 0 26 Feb 2021
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications Matthias Paulik M. Seigel Henry Mason Dominic Telaar Joris Kluivers ... Dominic Hughes O. Javidbakht Fei Dong Rehan Rishi Stanley Hung FedML 177 126 0 16 Feb 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 249 488 0 31 Dec 2020