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2020 – today
- 2024
[j4]Simiao Chen
, Xiaoge Deng, Dongpo Xu, Tao Sun, Dongsheng Li:
Decentralized stochastic sharpness-aware minimization algorithm. Neural Networks 176: 106325 (2024)- [c6]Xiaoge Deng, Tao Sun, Dongsheng Li, Xicheng Lu:
Exploring the Inefficiency of Heavy Ball as Momentum Parameter Approaches 1. IJCAI 2024: 3899-3907 - [i7]Ping Luo, Xiaoge Deng, Ziqing Wen, Tao Sun, Dongsheng Li:
Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients. CoRR abs/2403.16557 (2024) - [i6]Ziqing Wen, Xiaoge Deng, Ping Luo, Tao Sun, Dongsheng Li:
Score-based Generative Models with Adaptive Momentum. CoRR abs/2405.13726 (2024) - [i5]Ping Luo, Xiaoge Deng, Ziqing Wen, Tao Sun, Dongsheng Li:
Federated Prediction-Powered Inference from Decentralized Data. CoRR abs/2409.01730 (2024) - 2023
- [j3]Keshi Ge, Kai Lu, Yongquan Fu, Xiaoge Deng, Zhiquan Lai, Dongsheng Li:
Compressed Collective Sparse-Sketch for Distributed Data-Parallel Training of Deep Learning Models. IEEE J. Sel. Areas Commun. 41(4): 941-963 (2023) - [c5]Xiaoge Deng, Tao Sun, Shengwei Li, Dongsheng Li:
Stability-Based Generalization Analysis of the Asynchronous Decentralized SGD. AAAI 2023: 7340-7348 - [c4]Ziqing Wen, Xiaoge Deng, Tao Sun, Dongsheng Li:
Normalized Stochastic Heavy Ball with Adaptive Momentum. ECAI 2023: 2615-2622 - [i4]Shengwei Li, Zhiquan Lai, Yanqi Hao, Weijie Liu, Keshi Ge, Xiaoge Deng, Dongsheng Li, Kai Lu:
Automated Tensor Model Parallelism with Overlapped Communication for Efficient Foundation Model Training. CoRR abs/2305.16121 (2023) - [i3]Xiaoge Deng, Li Shen, Shengwei Li, Tao Sun, Dongsheng Li, Dacheng Tao:
Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent. CoRR abs/2308.09430 (2023) - 2022
- [c3]Keshi Ge, Yongquan Fu, Yiming Zhang, Zhiquan Lai, Xiaoge Deng, Dongsheng Li:
S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning. ICASSP 2022: 5233-5237 - 2021
- [c2]Keshi Ge, Yiming Zhang, Yongquan Fu, Zhiquan Lai, Xiaoge Deng, Dongsheng Li:
CASQ: Accelerate Distributed Deep Learning with Sketch-Based Gradient Quantization. CLUSTER 2021: 825-826 - [i2]Keshi Ge, Yongquan Fu, Zhiquan Lai, Xiaoge Deng, Dongsheng Li:
S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning. CoRR abs/2110.02140 (2021) - [i1]Xiaoge Deng, Tao Sun, Dongsheng Li:
SASG: Sparsification with Adaptive Stochastic Gradients for Communication-efficient Distributed Learning. CoRR abs/2112.04088 (2021) - 2020
- [j2]Xiaoge Deng, Tao Sun, Peibing Du, Dongsheng Li:
A Nonconvex Implementation of Sparse Subspace Clustering: Algorithm and Convergence Analysis. IEEE Access 8: 54741-54750 (2020) - [j1]Xiaoge Deng, Feng Liu, Feng Huang:
Linear Convergence Rate of Splitting Algorithms for Multi-Block Constrained Convex Minimizations. IEEE Access 8: 120694-120700 (2020) - [c1]Xiaoge Deng, Tao Sun, Feng Liu, Feng Huang:
PRIAG: Proximal Reweighted Incremental Aggregated Gradient Algorithm for Distributed Optimizations. ICA3PP (1) 2020: 495-511
Coauthor Index
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