Poster "distributed machine learning" Papers

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A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments

Siyuan Wu, Yongzhe Jia, Haolong Xiang et al.

NEURIPS 2025

Competitive Advantage Attacks to Decentralized Federated Learning

Yuqi Jia, Minghong Fang, Neil Gong

NEURIPS 2025arXiv:2310.13862
1
citations

Decentralized Optimization with Coupled Constraints

Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev et al.

ICLR 2025arXiv:2407.02020
2
citations

FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors

Changlong Shi, He Zhao, Bingjie Zhang et al.

CVPR 2025arXiv:2503.15842
7
citations

Multiplayer Federated Learning: Reaching Equilibrium with Less Communication

TaeHo Yoon, Sayantan Choudhury, Nicolas Loizou

NEURIPS 2025arXiv:2501.08263
5
citations

Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers

Ron Dorfman, Naseem Yehya, Kfir Levy

ICML 2024arXiv:2402.02951
5
citations

Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training

Tehila Dahan, Kfir Levy

ICML 2024arXiv:2405.14759
3
citations

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization

Shiwei Li, Wenchao Xu, Haozhao Wang et al.

ICML 2024arXiv:2408.03215
12
citations

Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks

Zach Robertson, Sanmi Koyejo

ICML 2024arXiv:2306.01870

Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training

Lin Lu, Chenxi Dai, Wangcheng Tao et al.

ICML 2024