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Shuheng Shen
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2020 – today
- 2024
- [c8]Jiajie Su
, Chaochao Chen
, Weiming Liu
, Zibin Lin
, Shuheng Shen
, Weiqiang Wang
, Xiaolin Zheng
:
Revisit Targeted Model Poisoning on Federated Recommendation: Optimize via Multi-objective Transport. SIGIR 2024: 1722-1732 - [i10]Dazhong Rong, Guoyao Yu, Shuheng Shen, Xinyi Fu, Peng Qian, Jianhai Chen, Qinming He, Xing Fu, Weiqiang Wang:
Clean-image Backdoor Attacks. CoRR abs/2403.15010 (2024) - [i9]Ke Wang, Tianyu Xia, Zhangxuan Gu, Yi Zhao, Shuheng Shen, Changhua Meng, Weiqiang Wang, Ke Xu:
E-ANT: A Large-Scale Dataset for Efficient Automatic GUI NavigaTion. CoRR abs/2406.14250 (2024) - [i8]Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen:
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. CoRR abs/2406.14288 (2024) - 2023
- [j5]Yifei Cheng
, Shuheng Shen, Xianfeng Liang, Jingchang Liu, Joya Chen, Tie Zhang, Enhong Chen:
Communication-efficient federated learning with stagewise training strategy. Neural Networks 167: 460-472 (2023) - [j4]Tianzhi Fang
, Yifan Zhang, Shuheng Shen, Hao Wu, Hao Liu, Huili Zhang:
High-Bandwidth Grid-Connected Inverter to Enhance System Robustness Against Weak Grid. IEEE Trans. Ind. Electron. 70(7): 6993-7003 (2023) - [c7]Tianyu Xia, Shuheng Shen, Su Yao, Xinyi Fu, Ke Xu, Xiaolong Xu, Xing Fu:
Differentially Private Learning with Per-Sample Adaptive Clipping. AAAI 2023: 10444-10452 - [c6]Xinting Liao
, Chaochao Chen
, Weiming Liu
, Pengyang Zhou
, Huabin Zhu
, Shuheng Shen
, Weiqiang Wang
, Mengling Hu
, Yanchao Tan
, Xiaolin Zheng
:
Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data. ACM Multimedia 2023: 1536-1545 - [i7]Xinting Liao, Chaochao Chen, Weiming Liu, Pengyang Zhou, Huabin Zhu, Shuheng Shen, Weiqiang Wang, Mengling Hu, Yanchao Tan, Xiaolin Zheng:
Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data. CoRR abs/2308.11646 (2023) - 2022
- [j3]Xianfeng Liang, Shuheng Shen, Enhong Chen, Jinchang Liu, Qi Liu, Yifei Cheng, Zhen Pan:
Accelerating local SGD for non-IID data using variance reduction. Frontiers Comput. Sci. 17(2): 172311 (2022) - [c5]Chengqiang Lu, Mingyang Yin, Shuheng Shen, Luo Ji, Qi Liu, Hongxia Yang:
Deep Unified Representation for Heterogeneous Recommendation. WWW 2022: 2141-2152 - [i6]Chengqiang Lu, Mingyang Yin, Shuheng Shen, Luo Ji, Qi Liu, Hongxia Yang:
Deep Unified Representation for Heterogeneous Recommendation. CoRR abs/2201.05861 (2022) - [i5]Tianyu Xia, Shuheng Shen, Su Yao, Xinyi Fu, Ke Xu, Xiaolong Xu, Xing Fu, Weiqiang Wang:
Differentially Private Learning with Per-Sample Adaptive Clipping. CoRR abs/2212.00328 (2022) - 2021
- [c4]Shuheng Shen, Yifei Cheng, Jingchang Liu, Linli Xu:
STL-SGD: Speeding Up Local SGD with Stagewise Communication Period. AAAI 2021: 9576-9584 - 2020
- [i4]Shuheng Shen, Yifei Cheng, Jingchang Liu, Linli Xu:
STL-SGD: Speeding Up Local SGD with Stagewise Communication Period. CoRR abs/2006.06377 (2020)
2010 – 2019
- 2019
- [j2]Jingchang Liu, Linli Xu, Shuheng Shen, Qing Ling:
An accelerated variance reducing stochastic method with Douglas-Rachford splitting. Mach. Learn. 108(5): 859-878 (2019) - [c3]Yinglin Jin, Tianzhi Fang, Shuheng Shen, Shushu Zhu:
Stability Analysis of Multi-Paralleled Grid-Connected Inverters with LCL-Filter in the Weak Grid. IECON 2019: 3937-3942 - [c2]Shuheng Shen, Linli Xu, Jingchang Liu, Xianfeng Liang, Yifei Cheng:
Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent. IJCAI 2019: 4582-4589 - [i3]Shuheng Shen, Linli Xu, Jingchang Liu, Xianfeng Liang, Yifei Cheng:
Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent. CoRR abs/1906.12043 (2019) - [i2]Xianfeng Liang, Shuheng Shen, Jingchang Liu, Zhen Pan, Enhong Chen, Yifei Cheng:
Variance Reduced Local SGD with Lower Communication Complexity. CoRR abs/1912.12844 (2019) - 2018
- [j1]Jingtang Liao, Shuheng Shen, Elmar Eisemann:
Depth annotations: Designing depth of a single image for depth-based effects. Comput. Graph. 71: 180-188 (2018) - [i1]Shuheng Shen, Linli Xu, Jingchang Liu, Junliang Guo, Qing Ling:
Asynchronous Stochastic Composition Optimization with Variance Reduction. CoRR abs/1811.06396 (2018) - 2017
- [c1]Jingtang Liao, Shuheng Shen, Elmar Eisemann:
Depth Map Design and Depth-based Effects With a Single Image. Graphics Interface 2017: 57-64
Coauthor Index
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last updated on 2024-08-08 20:15 CEST by the dblp team
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