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Federated Communication-Efficient Multi-Objective Optimization

21 October 2024

Papers citing "Federated Communication-Efficient Multi-Objective Optimization"

50 / 59 papers shown

Title
Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond Weiyu Chen Xiaoyuan Zhang Baijiong Lin Xi Lin Han Zhao Qingfu Zhang James T. Kwok 132 5 0 19 Jan 2025
Can Optimization Trajectories Explain Multi-Task Transfer? David Mueller Mark Dredze Nicholas Andrews 120 1 0 26 Aug 2024
Preference-Optimized Pareto Set Learning for Blackbox Optimization Zhang Haishan Diptesh Das Koji Tsuda 81 1 0 19 Aug 2024
FedAST: Federated Asynchronous Simultaneous Training Baris Askin Pranay Sharma Carlee Joe-Wong Gauri Joshi 80 2 0 01 Jun 2024
Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization Xi Lin Yilu Liu Xiao-Yan Zhang Fei Liu Zhenkun Wang Qingfu Zhang 87 5 0 30 May 2024
Many-Objective Multi-Solution Transport Ziyue Li Tian Li Virginia Smith Jeff Bilmes Dinesh Manocha 76 3 0 06 Mar 2024
PMGDA: A Preference-based Multiple Gradient Descent Algorithm Xiao-Yan Zhang Xi Lin Qingfu Zhang 63 7 0 14 Feb 2024
FedHCA $^2$ : Towards Hetero-Client Federated Multi-Task Learning Yuxiang Lu Suizhi Huang Yuwen Yang Shalayiding Sirejiding Yue Ding Hongtao Lu FedML 89 4 0 22 Nov 2023
Federated Multi-Objective Learning Haibo Yang Zhuqing Liu Jia-Wei Liu Chaosheng Dong Michinari Momma FedML 85 10 0 15 Oct 2023
Scalarization for Multi-Task and Multi-Domain Learning at Scale Amelie Royer Tijmen Blankevoort B. Bejnordi 76 18 0 13 Oct 2023
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective Yuzheng Hu Ruicheng Xian Qilong Wu Qiuling Fan Lang Yin Han Zhao 74 42 0 27 Aug 2023
FedBone: Towards Large-Scale Federated Multi-Task Learning Yiqiang Chen Teng Zhang Xinlong Jiang Qian Chen Chenlong Gao Wuliang Huang FedML AI4CE 85 11 0 30 Jun 2023
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance Lisha Chen H. Fernando Yiming Ying Tianyi Chen 61 25 0 31 May 2023
Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms Peiyao Xiao Hao Ban Kaiyi Ji 94 21 0 28 May 2023
FedExP: Speeding Up Federated Averaging via Extrapolation Divyansh Jhunjhunwala Shiqiang Wang Gauri Joshi FedML 57 61 0 23 Jan 2023
A Survey on Federated Recommendation Systems Zehua Sun Yonghui Xu Yang Liu Weiliang He Lanju Kong Fangzhao Wu Yiheng Jiang Li-zhen Cui FedML 98 68 0 27 Dec 2022
Multi-Objective GFlowNets Moksh Jain Sharath Chandra Raparthy Alex Hernandez-Garcia Jarrid Rector-Brooks Yoshua Bengio Santiago Miret Emmanuel Bengio 74 91 0 23 Oct 2022
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach H. Fernando Han Shen Miao Liu Subhajit Chaudhury K. Murugesan Tianyi Chen 79 9 0 23 Oct 2022
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models Nikolaos Dimitriadis P. Frossard Franccois Fleuret 71 25 0 18 Oct 2022
Pareto Set Learning for Expensive Multi-Objective Optimization Xi Lin Zhiyuan Yang Xiao-Yan Zhang Qingfu Zhang 79 60 0 16 Oct 2022
Do Current Multi-Task Optimization Methods in Deep Learning Even Help? Derrick Xin Behrooz Ghorbani Ankush Garg Orhan Firat Justin Gilmer MoMe 118 65 0 23 Sep 2022
PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm T. Basaklar S. Gumussoy Ümit Y. Ogras 48 41 0 16 Aug 2022
FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning Divyansh Jhunjhunwala Pranay Sharma Aushim Nagarkatti Gauri Joshi FedML 90 67 0 28 Jul 2022
Machine Learning Model Sizes and the Parameter Gap Pablo Villalobos J. Sevilla T. Besiroglu Lennart Heim A. Ho Marius Hobbhahn ALM ELM AI4CE 72 60 0 05 Jul 2022
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization Syrine Belakaria Aryan Deshwal Nitthilan Kanappan Jayakodi J. Doppa 69 83 0 12 Apr 2022
AUC Maximization in the Era of Big Data and AI: A Survey Tianbao Yang Yiming Ying 138 188 0 28 Mar 2022
Controllable Dynamic Multi-Task Architectures Dripta S. Raychaudhuri Yumin Suh S. Schulter Xiang Yu M. Faraki Amit K. Roy-Chowdhury Manmohan Chandraker 59 33 0 28 Mar 2022
LibMTL: A Python Library for Multi-Task Learning Baijiong Lin Yu Zhang OffRL AI4CE 60 38 0 27 Mar 2022
Towards Multi-Objective Statistically Fair Federated Learning Ninareh Mehrabi Cyprien de Lichy John McKay C. He William Campbell FedML 65 12 0 24 Jan 2022
In Defense of the Unitary Scalarization for Deep Multi-Task Learning Vitaly Kurin Alessandro De Palma Ilya Kostrikov Shimon Whiteson M. P. Kumar 82 75 0 11 Jan 2022
Federated Learning Based on Dynamic Regularization D. A. E. Acar Yue Zhao Ramon Matas Navarro Matthew Mattina P. Whatmough Venkatesh Saligrama FedML 76 781 0 08 Nov 2021
Conflict-Averse Gradient Descent for Multi-task Learning Bo Liu Xingchao Liu Xiaojie Jin Peter Stone Qiang Liu 98 318 0 26 Oct 2021
Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting Wei-wei Zhu Jiebo Luo Andrew D. White FedML 65 33 0 15 Sep 2021
Efficiently Identifying Task Groupings for Multi-Task Learning Christopher Fifty Ehsan Amid Zhe Zhao Tianhe Yu Rohan Anil Chelsea Finn 290 255 1 10 Sep 2021
Federated Multi-Task Learning under a Mixture of Distributions Othmane Marfoq Giovanni Neglia A. Bellet Laetitia Kameni Richard Vidal FedML 105 282 0 23 Aug 2021
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning Sen Cui Weishen Pan Jian Liang Changshui Zhang Fei Wang FedML 78 90 0 19 Aug 2021
Scalable Pareto Front Approximation for Deep Multi-Objective Learning Michael Ruchte Josif Grabocka 72 59 0 24 Mar 2021
Multi-Task Reinforcement Learning with Context-based Representations Shagun Sodhani Amy Zhang Joelle Pineau 84 191 0 11 Feb 2021
A Decentralized Multi-Objective Optimization Algorithm Maude-Josée Blondin Matthew T. Hale 41 6 0 09 Oct 2020
Multi-Task Learning with Deep Neural Networks: A Survey M. Crawshaw CVBM 217 625 0 10 Sep 2020
A Survey on Negative Transfer Wen Zhang Lingfei Deng Lei Zhang Dongrui Wu AAML 100 221 0 02 Sep 2020
Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing Jed Mills Jia Hu Geyong Min FedML 63 202 0 17 Jul 2020
Federated Learning Meets Multi-objective Optimization Zeou Hu Kiarash Shaloudegi Guojun Zhang Yaoliang Yu FedML 67 95 0 20 Jun 2020
Gradient Surgery for Multi-Task Learning Tianhe Yu Saurabh Kumar Abhishek Gupta Sergey Levine Karol Hausman Chelsea Finn 178 1,228 0 19 Jan 2020
Pareto Multi-Task Learning Xi Lin Hui-Ling Zhen Zhenhua Li Qingfu Zhang Sam Kwong 85 351 0 30 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 264 6,285 0 10 Dec 2019
Multi-Gradient Descent for Multi-Objective Recommender Systems Nikola Milojković Diego Antognini Giancarlo Bergamin Boi Faltings C. Musat 56 47 0 09 Dec 2019
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 256 774 0 28 Sep 2019
The stochastic multi-gradient algorithm for multi-objective optimization and its application to supervised machine learning Suyun Liu Luis Nunes Vicente 137 74 0 10 Jul 2019
Which Tasks Should Be Learned Together in Multi-task Learning? Trevor Scott Standley Amir Zamir Dawn Chen Leonidas Guibas Jitendra Malik Silvio Savarese 103 517 0 18 May 2019