Publications

You can also find my articles on my Google Scholar profile.

Pre-Prints

Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training

Published in Arxiv, 2024

Recommended citation: Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training. Arxiv. M. Shi*, Y. Zhou*, R. Yu, Z. Li, Z. Liang, X. Zhao, X. Peng, T Rajpurohit, R. Vedantam, W. Zhao, K. Wang, Y. You.
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Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation

Published in Arxiv, 2024

Recommended citation: Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation. Arxiv. X. Wu, J. Niu, X. Liu, M. Shi, G. Zhu, S. Tang
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A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training

Published in Arxiv, 2024

Recommended citation: A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training. Arxiv. K. Wang*, M. Shi*, Y. Zhou*,Z. Yuan, Y. Shang, X. Peng, H. Zhang, Y. You
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Conference Papers

Federated CINN Clustering for Accurate Clustered Federated Learning

Published in ICASSP 2024, 2024

Recommended citation: Federated CINN Clustering for Accurate Clustered Federated Learning. ICASSP 2024. Y. Zhou, M. Shi, Y. Tian, Y. Li, Q. Ye, J. Lv
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PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning

Published in NeurIPS 2023, 2023

Recommended citation: PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning. NeurIPS 2023. M. Shi, Y. Zhou, K. Wang, H. Zhang, S. Huang, Q. Ye, J. Lv
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Unconstrained Feature Model and Its General Geometric Patterns in Federated Learning: Local Subspace Minority Collapse

Published in ICONIP 2023, 2023

Recommended citation: Unconstrained Feature Model and Its General Geometric Patterns in Federated Learning: Local Subspace Minority Collapse. ICONIP 2023. M. Shi, Y. Zhou, Q. Ye, J. Lv
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Proposed FCCA utilizes a global encoder to transform each client’s private data into multivariate Gaussian distributions

Published in ICCV 2023, 2023

Recommended citation: Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence. ICCV 2023. Y. Zhou, M. Shi, Y. Li, Y. Sun, Q. Ye, J. Lv
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Mingjia Shi

Publications

Pre-Prints

Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training

Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation

A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training

Conference Papers

Federated CINN Clustering for Accurate Clustered Federated Learning

PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning

Unconstrained Feature Model and Its General Geometric Patterns in Federated Learning: Local Subspace Minority Collapse

Proposed FCCA utilizes a global encoder to transform each client’s private data into multivariate Gaussian distributions

Journal Articles

DeFTA: A Plug-and-Play Peer-to-Peer Decentralized Federated Learning Framework

DLB: a dynamic load balance strategy for distributed training of deep neural networks

FLSGD: free local SGD with parallel synchronization