Personalised Federated Learning On Heterogeneous Feature Spaces

26 January 2023

Papers citing "Personalised Federated Learning On Heterogeneous Feature Spaces"

50 / 52 papers shown

Title
FedFA: Federated Learning with Feature Anchors to Align Features and Classifiers for Heterogeneous Data Tailin Zhou Jun Zhang Danny H. K. Tsang FedML 79 61 0 17 Nov 2022
FedFM: Anchor-based Feature Matching for Data Heterogeneity in Federated Learning Rui Ye Zhenyang Ni Chenxin Xu Jianyu Wang Siheng Chen Yonina C. Eldar FedML 89 33 0 14 Oct 2022
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning Liam Collins Hamed Hassani Aryan Mokhtari Sanjay Shakkottai FedML 83 80 0 27 May 2022
Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Ramé Matthieu Kirchmeyer Thibaud Rahier A. Rakotomamonjy Patrick Gallinari Matthieu Cord OOD 256 138 0 19 May 2022
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization Junyuan Hong Haotao Wang Zhangyang Wang Jiayu Zhou FedML 58 57 0 18 Mar 2022
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning Wei-Ning Chen Christopher A. Choquette-Choo Peter Kairouz A. Suresh FedML 112 65 0 07 Mar 2022
Continual Horizontal Federated Learning for Heterogeneous Data Junki Mori Isamu Teranishi Ryo Furukawa FedML 39 12 0 04 Mar 2022
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution Ananya Kumar Aditi Raghunathan Robbie Jones Tengyu Ma Percy Liang OODD 132 685 0 21 Feb 2022
Architecture Agnostic Federated Learning for Neural Networks Disha Makhija Xing Han Nhat Ho Joydeep Ghosh FedML 105 42 0 15 Feb 2022
Parameterized Knowledge Transfer for Personalized Federated Learning Jie Zhang Song Guo Xiaosong Ma Yining Qi Wencao Xu Feijie Wu 92 182 0 04 Nov 2021
Differentially Private Sliced Wasserstein Distance A. Rakotomamonjy L. Ralaivola 59 24 0 05 Jul 2021
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent Jason M. Altschuler Sinho Chewi P. Gerber Austin J. Stromme 84 37 0 16 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 97 344 0 09 Jun 2021
FedBABU: Towards Enhanced Representation for Federated Image Classification Jaehoon Oh Sangmook Kim Se-Young Yun FedML 121 204 0 04 Jun 2021
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study D. Kollias V. Sharmanska Stefanos Zafeiriou CVBM 76 224 0 08 May 2021
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments Fan Mo Hamed Haddadi Kleomenis Katevas Eduard Marin Diego Perino N. Kourtellis FedML 126 248 0 29 Apr 2021
PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN Daniele Romanini A. Hall Pavlos Papadopoulos Tom Titcombe Abbas Ismail Tudor Cebere R. Sandmann Robin Roehm Michael A. Hoeh FedML MU 97 92 0 01 Apr 2021
Personalized Federated Learning using Hypernetworks Aviv Shamsian Aviv Navon Ethan Fetaya Gal Chechik FedML 118 337 0 08 Mar 2021
Multi-task Learning by Leveraging the Semantic Information Fan Zhou B. Chaib-draa Boyu Wang 65 12 0 03 Mar 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 335 878 0 01 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 1.0K 29,926 0 26 Feb 2021
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques Filip Hanzely Boxin Zhao Mladen Kolar FedML 90 53 0 19 Feb 2021
Exploiting Shared Representations for Personalized Federated Learning Liam Collins Hamed Hassani Aryan Mokhtari Sanjay Shakkottai FedML OOD 105 729 0 14 Feb 2021
Federated Reconstruction: Partially Local Federated Learning K. Singhal Hakim Sidahmed Zachary Garrett Shanshan Wu Keith Rush Sushant Prakash FedML 95 143 0 05 Feb 2021
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning Nick Angelou Ayoub Benaissa Bogdan Cebere William Clark A. Hall ... Pavlos Papadopoulos Robin Roehm R. Sandmann Phillipp Schoppmann Tom Titcombe 54 28 0 18 Nov 2020
Lower Bounds and Optimal Algorithms for Personalized Federated Learning Filip Hanzely Slavomír Hanzely Samuel Horváth Peter Richtárik FedML 125 190 0 05 Oct 2020
High-dimensional Gaussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm Maxime Vono N. Dobigeon P. Chainais 65 31 0 04 Oct 2020
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Enmao Diao Jie Ding Vahid Tarokh FedML 100 559 0 03 Oct 2020
TextCaps: a Dataset for Image Captioning with Reading Comprehension Oleksii Sidorov Ronghang Hu Marcus Rohrbach Amanpreet Singh 97 418 0 24 Mar 2020
Federated Learning of a Mixture of Global and Local Models Filip Hanzely Peter Richtárik FedML 87 386 0 10 Feb 2020
Learning Autoencoders with Relational Regularization Hongteng Xu Dixin Luo Ricardo Henao Svati Shah Lawrence Carin 97 43 0 07 Feb 2020
Gaussian-Smooth Optimal Transport: Metric Structure and Statistical Efficiency Ziv Goldfeld Kristjan Greenewald OT 66 41 0 24 Jan 2020
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 285 6,307 0 10 Dec 2019
Secure and Efficient Federated Transfer Learning Shreya Sharma C. Xing Yang Liu Yan Kang FedML 53 80 0 29 Oct 2019
Improving Federated Learning Personalization via Model Agnostic Meta Learning Yihan Jiang Jakub Konecný Keith Rush Sreeram Kannan FedML 90 602 0 27 Sep 2019
On Mutual Information Maximization for Representation Learning Michael Tschannen Josip Djolonga Paul Kishan Rubenstein Sylvain Gelly Mario Lucic SSL 186 502 0 31 Jul 2019
Adaptive Gradient-Based Meta-Learning Methods M. Khodak Maria-Florina Balcan Ameet Talwalkar FedML 111 356 0 06 Jun 2019
Learning Generative Models across Incomparable Spaces Charlotte Bunne David Alvarez-Melis Andreas Krause Stefanie Jegelka GAN 66 112 0 14 May 2019
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 192 5,247 0 14 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 158 1,424 0 03 Dec 2018
Gromov-Wasserstein Alignment of Word Embedding Spaces David Alvarez-Melis Tommi Jaakkola OT 58 328 0 31 Aug 2018
Towards Optimal Transport with Global Invariances David Alvarez-Melis Stefanie Jegelka Tommi Jaakkola OT 77 71 0 25 Jun 2018
Unsupervised Alignment of Embeddings with Wasserstein Procrustes Edouard Grave Armand Joulin Quentin Berthet 79 199 0 29 May 2018
Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions Boris Muzellec Marco Cuturi 73 79 0 19 May 2018
MOABB: Trustworthy algorithm benchmarking for BCIs V. Jayaram A. Barachant 53 180 0 16 May 2018
Computational Optimal Transport Gabriel Peyré Marco Cuturi OT 244 2,158 0 01 Mar 2018
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption Stephen Hardy Wilko Henecka Hamish Ivey-Law Richard Nock Giorgio Patrini Guillaume Smith Brian Thorne FedML 79 536 0 29 Nov 2017
Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning Werner Zellinger Thomas Grubinger E. Lughofer T. Natschläger Susanne Saminger-Platz OOD 108 580 0 28 Feb 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 417 17,653 0 17 Feb 2016
Limit laws of the empirical Wasserstein distance: Gaussian distributions Thomas Rippl Axel Munk A. Sturm 121 64 0 15 Jul 2015