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ORCIDYue Cheng 0001
- > Home > Persons > Yue Cheng 0001
Publications
- 2025
[c37]Guangji Bai, Ziyang Yu, Zheng Chai, Yue Cheng, Liang Zhao:
Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction. SDM 2025: 578-587- 2024
- [j6]Junxiang Wang
, Hongyi Li, Zheng Chai, Yongchao Wang, Yue Cheng, Liang Zhao:
Toward Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4491-4501 (2024) - [i21]Guangji Bai, Zheng Chai, Chen Ling, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu, Mengdan Zhu, Yifei Zhang, Carl Yang, Yue Cheng, Liang Zhao:
Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models. CoRR abs/2401.00625 (2024) - 2023
- [i16]Guangji Bai, Ziyang Yu, Zheng Chai, Yue Cheng, Liang Zhao:
Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction. CoRR abs/2308.13466 (2023) - 2022
- [i14]Zheng Chai, Guangji Bai, Liang Zhao, Yue Cheng:
Distributed Graph Neural Network Training with Periodic Historical Embedding Synchronization. CoRR abs/2206.00057 (2022) - 2021
- [c27]Yujing Chen, Zheng Chai, Yue Cheng, Huzefa Rangwala:
Asynchronous Federated Learning for Sensor Data with Concept Drift. IEEE BigData 2021: 4822-4831 - [c25]Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala:
FedAT: a high-performance and communication-efficient federated learning system with asynchronous tiers. SC 2021: 60 - [i11]Junxiang Wang, Hongyi Li, Zheng Chai, Yongchao Wang, Yue Cheng, Liang Zhao:
Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework. CoRR abs/2105.09837 (2021) - [i9]Yujing Chen, Zheng Chai, Yue Cheng, Huzefa Rangwala:
Asynchronous Federated Learning for Sensor Data with Concept Drift. CoRR abs/2109.00151 (2021) - 2020
- [c21]Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng:
TiFL: A Tier-based Federated Learning System. HPDC 2020: 125-136 - [c20]Junxiang Wang, Zheng Chai, Yue Cheng, Liang Zhao:
Toward Model Parallelism for Deep Neural Network based on Gradient-free ADMM Framework. ICDM 2020: 591-600 - [i7]Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng:
TiFL: A Tier-based Federated Learning System. CoRR abs/2001.09249 (2020) - [i5]Junxiang Wang, Zheng Chai, Yue Cheng, Liang Zhao:
Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training. CoRR abs/2009.04053 (2020) - [i4]Zheng Chai, Yujing Chen, Liang Zhao, Yue Cheng, Huzefa Rangwala:
FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data. CoRR abs/2010.05958 (2020) - 2019
- [c18]Zheng Chai, Hannan Fayyaz, Zeshan Fayyaz, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig, Yue Cheng:
Towards Taming the Resource and Data Heterogeneity in Federated Learning. OpML 2019: 19-21 - 2018
- [c15]Yue Cheng, Zheng Chai, Ali Anwar:
Characterizing Co-located Datacenter Workloads: An Alibaba Case Study. APSys 2018: 12:1-12:3 - [i1]Yue Cheng, Zheng Chai, Ali Anwar:
Characterizing Co-located Datacenter Workloads: An Alibaba Case Study. CoRR abs/1808.02919 (2018)
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