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2020 – today
- 2025
[c12]Liangliang Shi, Haoran Zhang
, Shuheng Shen, Changhua Meng, Weiqiang Wang, Junchi Yan:
BiQAP: Neural Bi-level Optimization-based Framework for Solving Quadratic Assignment Problems. KDD (2) 2025: 2550-2561- [c11]Zheng Gong, Shuheng Shen, Changhua Meng, Ying Sun:
Exploring Hypergraph Condensation via Variational Hyperedge Generation and Multi-Aspectual Amelioration. WWW 2025: 1248-1260 - [i12]Fei Tang, Zhangxuan Gu, Zhengxi Lu, Xuyang Liu, Shuheng Shen, Changhua Meng, Wen Wang, Wenqi Zhang, Yongliang Shen, Weiming Lu, Jun Xiao, Yueting Zhuang:
GUI-G2: Gaussian Reward Modeling for GUI Grounding. CoRR abs/2507.15846 (2025) - [i11]Zhangxuan Gu, Zhengwen Zeng, Zhenyu Xu, Xingran Zhou, Shuheng Shen, Yunfei Liu, Beitong Zhou, Changhua Meng, Tianyu Xia, Weizhi Chen, Yue Wen, Jingya Dou, Fei Tang, Jinzhen Lin, Yulin Liu, Zhenlin Guo, Yichen Gong, Heng Jia, Changlong Gao, Yuan Guo, Yong Deng, Zhenyu Guo, Liang Chen, Weiqiang Wang:
UI-Venus Technical Report: Building High-performance UI Agents with RFT. CoRR abs/2508.10833 (2025) - 2024
- [c10]Dazhong Rong, Guoyao Yu, Shuheng Shen, Xinyi Fu, Peng Qian, Jianhai Chen, Qinming He, Xing Fu, Weiqiang Wang:
Clean-Image Backdoor Attacks. ICANN (10) 2024: 187-202 - [c9]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. KDD 2024: 1968-1979 - [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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