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An Enhanced Gradient-Tracking Bound for Distributed Online Stochastic Convex Optimization
S. A. Alghunaim and K. Yuan
Signal Processing
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Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
Y. He , X. Huang, and K. Yuan
The Conference on Neural Information Processing Systems (NeurIPS)
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Removing data heterogeneity influence enhances network topology dependence of decentralized SGD
K. Yuan, S. A. Alghunaim, and X. Huang
Journal of Machine Learning Research (JMLR)
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Achieving Linear Speedup with Network-Independent Learning Rates in Decentralized Stochastic Optimization
H. Yuan, S. A. Alghunaim, and K. Yuan
IEEE Conference on Decision and Control (CDC)
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On the Performance of Gradient Tracking with Local Updates
E. D. H. Nguyen, S. A. Alghunaim, K. Yuan, and C. A. Uribe
IEEE Conference on Decision and Control (CDC)
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DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm
L. Ding, K. Jin, B. Ying, K. Yuan, and W. Yin
The International Conference on Machine Learning (ICML)
[Code]
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AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
Y.-F. Zhang, X. Wang, K. Jin, K. Yuan, Z. Zhang, L. Wang, R. Jin, and T. Tan
The International Conference on Machine Learning (ICML)
[Code]
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BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection
L. Yang, K. Yu, T. Tang, J. Li, K. Yuan, L. Wang, X. Zhang, and P. Chen
The IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR)
[Code]
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Revisiting optimal convergence rate for smooth and non-convex stochastic decentralized optimization
K. Yuan, X. Huang, Y. Chen, X. Zhang, Y. Zhang, and P. Pan
The Conference on Neural Information Processing Systems (NeurIPS)
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Communication-efficient topologies for decentralized learning with O(1) consensus rate
Z. Song, W. Li, K. Jin, L. Shi, M. Yan, W. Yin, and K. Yuan
The Conference on Neural Information Processing Systems (NeurIPS)
[Code] [Poster] [5-min video presentation]
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Lower bounds and nearly optimal algorithms in distributed learning with communication compression
X. Huang, Y. Chen, W. Yin, and K. Yuan
The Conference on Neural Information Processing Systems (NeurIPS)
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A unified and refined convergence analysis for non-convex decentralized learning
S. A. Alghunaim and K. Yuan
IEEE Transactions on Signal Processing
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A Byzantine-resilient dual subgradient method for vertical federated learning
K. Yuan, Z. Wu, and Q. Ling
The IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
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CHEX: Channel exploration for CNN model compression
Z. Hou, M. Qin, F. Sun, X. Ma, K. Yuan, Y. Xu, Y.-K. Chen, R. Jin, Y. Xie, and S.-Y. Kung
The IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR)
[Code]
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Effective model sparsification by scheduled Grow-and-Prune methods
X. Ma, M. Qin, F. Sun, Z. Hou, K. Yuan, Y. Xu, Y. Wang, Y.-K. Chen, R. Jin, and Y. Xie
The International Conference on Learning Representations (ICLR)
[Code]