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Xiangyi Chen
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2020 – today
- 2024
- [j10]Tianao Xiang, Yuanguo Bi, Xiangyi Chen, Yuan Liu, Boyang Wang, Xuemin Shen, Xingwei Wang:
Federated Learning With Dynamic Epoch Adjustment and Collaborative Training in Mobile Edge Computing. IEEE Trans. Mob. Comput. 23(5): 4092-4106 (2024) - [j9]Yufei Liu, Yuanguo Bi, Xiaoming Yuan, Dusit Niyato, Kaiqi Yang, Xiangyi Chen, Liang Zhao:
A Novel Multimodal Long-Term Trajectory Prediction Scheme for Heterogeneous User Behavior Patterns. IEEE Trans. Mob. Comput. 23(12): 13275-13291 (2024) - [c17]Kungang Li, Xiangyi Chen, Ling Leng, Jiajing Xu, Jiankai Sun, Behnam Rezaei:
Privacy Preserving Conversion Modeling in Data Clean Room. RecSys 2024: 819-822 - 2023
- [j8]Xiangyi Chen, Guangjie Han, Yuanguo Bi, Zimeng Yuan, Mahesh K. Marina, Yufei Liu, Hai Zhao:
Traffic Prediction-Assisted Federated Deep Reinforcement Learning for Service Migration in Digital Twins-Enabled MEC Networks. IEEE J. Sel. Areas Commun. 41(10): 3212-3229 (2023) - [c16]Xiangyi Chen, Stéphane Lathuilière:
Face Aging via Diffusion-based Editing. BMVC 2023: 595 - [i12]Xiangyi Chen, Stéphane Lathuilière:
Face Aging via Diffusion-based Editing. CoRR abs/2309.11321 (2023) - 2022
- [j7]Xiangyi Chen, Yuanguo Bi, Xueping Chen, Hai Zhao, Nan Cheng, Fuliang Li, Wenlin Cheng:
Dynamic Service Migration and Request Routing for Microservice in Multicell Mobile-Edge Computing. IEEE Internet Things J. 9(15): 13126-13143 (2022) - [j6]Xiangyi Chen, Yuanguo Bi, Guangjie Han, Dongyu Zhang, Minghan Liu, Han Shi, Hai Zhao, Fengyun Li:
Distributed Computation Offloading and Trajectory Optimization in Multi-UAV-Enabled Edge Computing. IEEE Internet Things J. 9(20): 20096-20110 (2022) - [j5]Deyu Yan, Genhui Zheng, Caicui Wang, Zikun Chen, Tiantian Mao, Jian Gao, Yu Yan, Xiangyi Chen, Xuejie Ji, Jinyu Yu, Saifeng Mo, Haonan Wen, Wenhao Han, Mengdi Zhou, Yuan Wang, Jun Wang, Kailin Tang, Zhiwei Cao:
HIT 2.0: an enhanced platform for Herbal Ingredients' Targets. Nucleic Acids Res. 50(D1): 1238-1243 (2022) - [c15]Xiangyi Chen, Belhal Karimi, Weijie Zhao, Ping Li:
On the Convergence of Decentralized Adaptive Gradient Methods. ACML 2022: 217-232 - [c14]Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi:
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. ICML 2022: 26048-26067 - [c13]Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu:
Distributed adversarial training to robustify deep neural networks at scale. UAI 2022: 2353-2363 - [i11]Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu:
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale. CoRR abs/2206.06257 (2022) - 2021
- [j4]Xiangyi Chen, Xingwei Wang, Bo Yi, Qiang He, Min Huang:
Deep Learning-Based Traffic Prediction for Energy Efficiency Optimization in Software-Defined Networking. IEEE Syst. J. 15(4): 5583-5594 (2021) - [i10]Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Jinfeng Yi:
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. CoRR abs/2106.13673 (2021) - [i9]Xiangyi Chen, Belhal Karimi, Weijie Zhao, Ping Li:
On the Convergence of Decentralized Adaptive Gradient Methods. CoRR abs/2109.03194 (2021) - [i8]Xiangyi Chen, Xiaoyun Li, Ping Li:
Toward Communication Efficient Adaptive Gradient Method. CoRR abs/2109.05109 (2021) - 2020
- [c12]Xiangyi Chen, Xiaoyun Li, Ping Li:
Toward Communication Efficient Adaptive Gradient Method. FODS 2020: 119-128 - [c11]Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly:
Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks. ICML 2020: 6282-6293 - [c10]Xiangyi Chen, Tiancong Chen, Haoran Sun, Zhiwei Steven Wu, Mingyi Hong:
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms. NeurIPS 2020 - [c9]Xiangyi Chen, Zhiwei Steven Wu, Mingyi Hong:
Understanding Gradient Clipping in Private SGD: A Geometric Perspective. NeurIPS 2020 - [i7]Yingxue Zhou, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Arindam Banerjee:
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds. CoRR abs/2006.13501 (2020) - [i6]Xiangyi Chen, Zhiwei Steven Wu, Mingyi Hong:
Understanding Gradient Clipping in Private SGD: A Geometric Perspective. CoRR abs/2006.15429 (2020)
2010 – 2019
- 2019
- [c8]Songtao Lu, Rahul Singh, Xiangyi Chen, Yongxin Chen, Mingyi Hong:
Alternating Gradient Descent Ascent for Nonconvex Min-Max Problems in Robust Learning and GANs. ACSSC 2019: 680-684 - [c7]Xiangyi Chen, Sijia Liu, Ruoyu Sun, Mingyi Hong:
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization. ICLR (Poster) 2019 - [c6]Sijia Liu, Pin-Yu Chen, Xiangyi Chen, Mingyi Hong:
signSGD via Zeroth-Order Oracle. ICLR (Poster) 2019 - [c5]Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox:
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. NeurIPS 2019: 7202-7213 - [i5]Xiangyi Chen, Tiancong Chen, Haoran Sun, Zhiwei Steven Wu, Mingyi Hong:
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms. CoRR abs/1906.01736 (2019) - [i4]Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly:
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML. CoRR abs/1909.13806 (2019) - [i3]Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox:
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. CoRR abs/1910.06513 (2019) - 2018
- [j3]Haoran Sun, Xiangyi Chen, Qingjiang Shi, Mingyi Hong, Xiao Fu, Nicholas D. Sidiropoulos:
Learning to Optimize: Training Deep Neural Networks for Interference Management. IEEE Trans. Signal Process. 66(20): 5438-5453 (2018) - [j2]Mingjie Zhao, Xiangyi Chen, Qingjiang Shi, WeiQiang Xu:
Joint Transmit Beamforming and Antenna Selection in MIMO Systems. IEEE Wirel. Commun. Lett. 7(5): 716-719 (2018) - [i2]Xiangyi Chen, Sijia Liu, Ruoyu Sun, Mingyi Hong:
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization. CoRR abs/1808.02941 (2018) - 2017
- [c4]Xiangyi Chen, Liangmin Wang:
Secret-Sharing Approach for Detecting Compromised Mobile Sink in Unattended Wireless Sensor Networks. MSN 2017: 303-317 - [c3]Haoran Sun, Xiangyi Chen, Qingjiang Shi, Mingyi Hong, Xiao Fu, Nikos D. Sidiropoulos:
Learning to optimize: Training deep neural networks for wireless resource management. SPAWC 2017: 1-6 - [i1]Haoran Sun, Xiangyi Chen, Qingjiang Shi, Mingyi Hong, Xiao Fu, Nikos D. Sidiropoulos:
Learning to Optimize: Training Deep Neural Networks for Wireless Resource Management. CoRR abs/1705.09412 (2017) - 2013
- [j1]Xiangyi Chen, Lixia Meng, Yong-Zhao Zhan:
Detecting and Defending against Replication Attacks in Wireless Sensor Networks. Int. J. Distributed Sens. Networks 9 (2013)
2000 – 2009
- 2009
- [c2]Xiangyi Chen, Chen Ding:
Rank Aggregation to Combine QoS in Web Search. APWeb/WAIM 2009: 186-197 - 2008
- [c1]Xiangyi Chen, Chen Ding:
QoS Based Ranking for Web Search. Web Intelligence 2008: 747-750
Coauthor Index
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