FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion

27 October 2024

Papers citing "FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion"

42 / 42 papers shown

Title
One-shot Federated Learning Methods: A Practical Guide Xiang Liu Zhenheng Tang Xia Li Yijun Song Sijie Ji Zemin Liu Bo Han Linshan Jiang Jialin Li FedML 110 1 0 13 Feb 2025
Robust Training of Federated Models with Extremely Label Deficiency Yonggang Zhang Zhiqin Yang Xinmei Tian Nannan Wang Tongliang Liu Bo Han FedML 94 6 0 22 Feb 2024
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training Zhenheng Tang Xiaowen Chu Ryan Yide Ran Sunwoo Lee Shaoshuai Shi Yonggang Zhang Yuxin Wang Alex Liang A. Avestimehr Chaoyang He FedML 46 10 0 03 Mar 2023
DoCoFL: Downlink Compression for Cross-Device Federated Learning Ron Dorfman S. Vargaftik Y. Ben-Itzhak Kfir Y. Levy FedML 44 20 0 01 Feb 2023
Tackling Data Heterogeneity in Federated Learning with Class Prototypes Yutong Dai Zhenpeng Chen Junnan Li Shelby Heinecke Lichao Sun Ran Xu FedML 48 82 0 06 Dec 2022
On Feature Learning in the Presence of Spurious Correlations Pavel Izmailov Polina Kirichenko Nate Gruver A. Wilson 49 126 0 20 Oct 2022
Git Re-Basin: Merging Models modulo Permutation Symmetries Samuel K. Ainsworth J. Hayase S. Srinivasa MoMe 264 326 0 11 Sep 2022
Federated Learning with Label Distribution Skew via Logits Calibration Jie M. Zhang Zhiqi Li Yue Liu Jianghe Xu Shuang Wu Shouhong Ding Chao Wu FedML 50 141 0 01 Sep 2022
Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring Zhengquan Luo Yunlong Wang Zilei Wang Zhenan Sun Tieniu Tan FedML 24 43 0 14 Jun 2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning Zhenheng Tang Yonggang Zhang Shaoshuai Shi Xinfu He Bo Han Xiaowen Chu FedML 56 74 0 06 Jun 2022
Federated Class-Incremental Learning Jiahua Dong Lixu Wang Zhen Fang Gan Sun Shichao Xu Tianlin Li Qi Zhu CLL FedML 49 175 0 22 Mar 2022
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution Ananya Kumar Aditi Raghunathan Robbie Jones Tengyu Ma Percy Liang OODD 62 655 0 21 Feb 2022
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks Chaoyang He Alay Dilipbhai Shah Zhenheng Tang Adarshan Naiynar Sivashunmugam Keerti Bhogaraju Mita Shimpi Li Shen Xiaowen Chu Mahdi Soltanolkotabi Salman Avestimehr VLM FedML 65 68 0 22 Nov 2021
FairFed: Enabling Group Fairness in Federated Learning Yahya H. Ezzeldin Shen Yan Chaoyang He Emilio Ferrara A. Avestimehr FedML 45 206 0 02 Oct 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization Kartik Ahuja Ethan Caballero Dinghuai Zhang Jean-Christophe Gagnon-Audet Yoshua Bengio Ioannis Mitliagkas Irina Rish OOD 30 258 0 11 Jun 2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data Mi Luo Fei Chen Dapeng Hu Yifan Zhang Jian Liang Jiashi Feng FedML 58 332 0 09 Jun 2021
Towards a Theoretical Framework of Out-of-Distribution Generalization Haotian Ye Chuanlong Xie Tianle Cai Ruichen Li Zhenguo Li Liwei Wang OODD OOD 70 108 0 08 Jun 2021
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? Dinghuai Zhang Kartik Ahuja Yilun Xu Yisen Wang Aaron Courville OOD 41 96 0 05 Jun 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 282 855 0 01 Mar 2021
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective Kartik Ahuja Jun Wang Amit Dhurandhar Karthikeyan Shanmugam Kush R. Varshney OOD 48 79 0 30 Oct 2020
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms Maruan Al-Shedivat Jennifer Gillenwater Eric Xing Afshin Rostamizadeh FedML 68 109 0 11 Oct 2020
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning Hong-You Chen Wei-Lun Chao FedML 27 259 0 04 Sep 2020
What is being transferred in transfer learning? Behnam Neyshabur Hanie Sedghi Chiyuan Zhang 47 513 0 26 Aug 2020
A Self-supervised Approach for Adversarial Robustness Muzammal Naseer Salman Khan Munawar Hayat Fahad Shahbaz Khan Fatih Porikli AAML 40 254 0 08 Jun 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 359 41,106 0 28 May 2020
What Makes for Good Views for Contrastive Learning? Yonglong Tian Chen Sun Ben Poole Dilip Krishnan Cordelia Schmid Phillip Isola SSL 53 1,313 0 20 May 2020
SplitFed: When Federated Learning Meets Split Learning Chandra Thapa Pathum Chamikara Mahawaga Arachchige S. Çamtepe Lichao Sun FedML 57 573 0 25 Apr 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 126 2,023 0 16 Apr 2020
Federated Visual Classification with Real-World Data Distribution T. Hsu Qi Matthew Brown FedML 103 199 0 18 Mar 2020
Think Locally, Act Globally: Federated Learning with Local and Global Representations Paul Pu Liang Terrance Liu Liu Ziyin Nicholas B. Allen Randy P. Auerbach David Brent Ruslan Salakhutdinov Louis-Philippe Morency FedML 62 554 0 06 Jan 2020
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer Hong Chang Virat Shejwalkar Reza Shokri Amir Houmansadr FedML 47 167 0 24 Dec 2019
FedMD: Heterogenous Federated Learning via Model Distillation Daliang Li Junpu Wang FedML 67 845 0 08 Oct 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 47 454 0 26 Sep 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 99 1,128 0 13 Sep 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 153 1,454 0 16 Jul 2019
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 111 1,461 0 10 May 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 59 505 0 13 Mar 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 130 3,433 0 09 Mar 2018
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 76 1,399 0 31 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 86 8,807 0 25 Aug 2017
Overcoming catastrophic forgetting in neural networks J. Kirkpatrick Razvan Pascanu Neil C. Rabinowitz J. Veness Guillaume Desjardins ... A. Grabska-Barwinska Demis Hassabis Claudia Clopath D. Kumaran R. Hadsell CLL 194 7,410 0 02 Dec 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 249 4,620 0 18 Oct 2016