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Shiqiang Wang 0001

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affiliation: IBM Thomas J. Watson Research Center, Yorktown Heights, USA
affiliation (PhD 2015): Imperial College London, Department of Electrical and Electronic Engineering, UK

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2025
[j33]
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Chong Yu, Shuaiqi Shen, Shiqiang Wang, Kuan Zhang, Hai Zhao:
Communication-Efficient Hybrid Federated Learning for E-Health With Horizontal and Vertical Data Partitioning. IEEE Trans. Neural Networks Learn. Syst. 36(3): 5614-5628 (2025)
2024
[j32]
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Bing Luo, Wenli Xiao, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Adaptive Heterogeneous Client Sampling for Federated Learning Over Wireless Networks. IEEE Trans. Mob. Comput. 23(10): 9663-9677 (2024)
[j31]
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Timothy Castiglia, Shiqiang Wang, Stacy Patterson:
Flexible Vertical Federated Learning With Heterogeneous Parties. IEEE Trans. Neural Networks Learn. Syst. 35(12): 17878-17892 (2024)
[j30]
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Xiaonan Liu, Shiqiang Wang, Yansha Deng, Arumugam Nallanathan:
Adaptive Federated Pruning in Hierarchical Wireless Networks. IEEE Trans. Wirel. Commun. 23(6): 5985-5999 (2024)
2023
[j29]
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Cho-Chun Chiu, Xusheng Zhang, Ting He, Shiqiang Wang, Ananthram Swami:
Laplacian Matrix Sampling for Communication- Efficient Decentralized Learning. IEEE J. Sel. Areas Commun. 41(4): 887-901 (2023)
[j28]
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Zheyu Chen, Kin K. Leung, Shiqiang Wang, Leandros Tassiulas, Kevin S. Chan, Don Towsley:
Use Coupled LSTM Networks to Solve Constrained Optimization Problems. IEEE Trans. Cogn. Commun. Netw. 9(2): 304-316 (2023)
[j27]
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Yuang Jiang, Shiqiang Wang, Víctor Valls, Bong Jun Ko, Wei-Han Lee, Kin K. Leung, Leandros Tassiulas:
Model Pruning Enables Efficient Federated Learning on Edge Devices. IEEE Trans. Neural Networks Learn. Syst. 34(12): 10374-10386 (2023)
[j26]
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Shihao Shen, Yiwen Han, Xiaofei Wang, Shiqiang Wang, Victor C. M. Leung:
Collaborative Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud Network. IEEE/ACM Trans. Netw. 31(6): 2950-2964 (2023)
2022
[j25]
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Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini:
A Survey on Federated Learning for Resource-Constrained IoT Devices. IEEE Internet Things J. 9(1): 1-24 (2022)
[j24]
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Anirban Das, Timothy Castiglia, Shiqiang Wang, Stacy Patterson:
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning. ACM Trans. Intell. Syst. Technol. 13(6): 99:1-99:27 (2022)
[j23]
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Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris:
Communication-Efficient $k$k-Means for Edge-Based Machine Learning. IEEE Trans. Parallel Distributed Syst. 33(10): 2509-2523 (2022)
2021
[j22]
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Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Cost-Effective Federated Learning in Mobile Edge Networks. IEEE J. Sel. Areas Commun. 39(12): 3606-3621 (2021)
[j21]
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Shiqiang Wang:
Efficient deep learning. Nat. Comput. Sci. 1(3): 181-182 (2021)
[j20]
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Jun Huang, Jalel Ben-Othman, Shiqiang Wang, Ricky Yu-Kwong Kwok, Victor C. M. Leung, Wei Sun:
Guest Editorial: AI-Empowered Mobile Edge Computing in the Internet of Vehicles. IEEE Netw. 35(3): 72-73 (2021)
[j19]
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Vajiheh Farhadi, Fidan Mehmeti, Ting He, Thomas F. La Porta, Hana Khamfroush, Shiqiang Wang, Kevin S. Chan, Konstantinos Poularakis:
Service Placement and Request Scheduling for Data-Intensive Applications in Edge Clouds. IEEE/ACM Trans. Netw. 29(2): 779-792 (2021)
2020
[j18]
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Hanlin Lu, Ming-Ju Li, Ting He, Shiqiang Wang, Vijaykrishnan Narayanan, Kevin S. Chan:
Robust Coreset Construction for Distributed Machine Learning. IEEE J. Sel. Areas Commun. 38(10): 2400-2417 (2020)
[j17]
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Yilei Lin, Ting He, Shiqiang Wang, Kevin Chan, Stephen Pasteris:
Looking Glass of NFV: Inferring the Structure and State of NFV Network From External Observations. IEEE/ACM Trans. Netw. 28(4): 1477-1490 (2020)
2019
[j16]
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Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis, Kin K. Leung, Christian Makaya, Ting He, Kevin Chan:
Adaptive Federated Learning in Resource Constrained Edge Computing Systems. IEEE J. Sel. Areas Commun. 37(6): 1205-1221 (2019)
[j15]
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Changchang Liu, Xi He, Thee Chanyaswad, Shiqiang Wang, Prateek Mittal:
Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing. Proc. Priv. Enhancing Technol. 2019(3): 233-254 (2019)
[j14]
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Shiqiang Wang, Rahul Urgaonkar, Murtaza Zafer, Ting He, Kevin Chan, Kin K. Leung:
Dynamic Service Migration in Mobile Edge Computing Based on Markov Decision Process. IEEE/ACM Trans. Netw. 27(3): 1272-1288 (2019)
2018
[j13]
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Tao Zhao, I-Hong Hou, Shiqiang Wang, Kevin Chan:
Red/LeD: An Asymptotically Optimal and Scalable Online Algorithm for Service Caching at the Edge. IEEE J. Sel. Areas Commun. 36(8): 1857-1870 (2018)
[j12]
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Andrew Machen, Shiqiang Wang, Kin K. Leung, Bong Jun Ko, Theodoros Salonidis:
Live Service Migration in Mobile Edge Clouds. IEEE Wirel. Commun. 25(1): 140-147 (2018)
2017
[j11]
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Shiqiang Wang, Murtaza Zafer, Kin K. Leung:
Online Placement of Multi-Component Applications in Edge Computing Environments. IEEE Access 5: 2514-2533 (2017)
[j10]
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Ting He, Ertugrul Necdet Ciftcioglu, Shiqiang Wang, Kevin S. Chan:
Location Privacy in Mobile Edge Clouds: A Chaff-Based Approach. IEEE J. Sel. Areas Commun. 35(11): 2625-2636 (2017)
[j9]
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Shiqiang Wang, Rahul Urgaonkar, Ting He, Kevin Chan, Murtaza Zafer, Kin K. Leung:
Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs. IEEE Trans. Parallel Distributed Syst. 28(4): 1002-1016 (2017)
2016
[j8]
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Fanzhao Wang, Lei Guo, Shiqiang Wang, Qingyang Song, Abbas Jamalipour:
Approaching Single-Hop Performance in Multihop Networks: End-to-End Known-Interference Cancelation (E2E-KIC). IEEE Trans. Veh. Technol. 65(9): 7606-7620 (2016)
2015
[j7]
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Rahul Urgaonkar, Shiqiang Wang, Ting He, Murtaza Zafer, Kevin S. Chan, Kin K. Leung:
Dynamic service migration and workload scheduling in edge-clouds. Perform. Evaluation 91: 205-228 (2015)
2014
[j6]
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Qingyang Song, Lei Guo, Fanzhao Wang, Shiqiang Wang, Abbas Jamalipour:
MAC-centric cross-layer collaboration: a case study on physical-layer network coding. IEEE Wirel. Commun. 21(6): 160-166 (2014)
2013
[j5]
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Shiqiang Wang, Qingyang Song, Xingwei Wang, Abbas Jamalipour:
Distributed MAC Protocol Supporting Physical-Layer Network Coding. IEEE Trans. Mob. Comput. 12(5): 1023-1036 (2013)
[j4]
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Yang Huang, Shiqiang Wang, Qingyang Song, Lei Guo, Abbas Jamalipour:
Synchronous Physical-Layer Network Coding: A Feasibility Study. IEEE Trans. Wirel. Commun. 12(8): 4048-4057 (2013)
2012
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Fanzhao Wang, Shiqiang Wang, Qingyang Song, Lei Guo:
Adaptive Relaying Method Selection for Multi-Rate Wireless Networks with Network Coding. IEEE Commun. Lett. 16(12): 2004-2007 (2012)
[j2]
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Qingyang Song, Zhaolong Ning, Shiqiang Wang, Abbas Jamalipour:
Link stability estimation based on link connectivity changes in mobile ad-hoc networks. J. Netw. Comput. Appl. 35(6): 2051-2058 (2012)
2011
[j1]
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Shiqiang Wang, Qingyang Song, Xingwei Wang, Abbas Jamalipour:
Rate and Power Adaptation for Analog Network Coding. IEEE Trans. Veh. Technol. 60(5): 2302-2313 (2011)

Conference and Workshop Papers

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2025
[c86]
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Daouda Sow, Herbert Woisetschläger, Saikiran Bulusu, Shiqiang Wang, Hans-Arno Jacobsen, Yingbin Liang:
Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining. ICLR 2025
2024
[c85]
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Guojun Xiong, Gang Yan, Shiqiang Wang, Jian Li:
DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations. AAAI 2024: 16103-16111
[c84]
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Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning. AISTATS 2024: 1612-1620
[c83]
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Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen:
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly. DEEM@SIGMOD 2024: 39-50
[c82]
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Hanjing Wang, Shiqiang Wang, Qiang Ji:
Semantic Attribution for Explainable Uncertainty Quantification. Epi UAI 2024: 101-112
[c81]
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Shiqiang Wang, Mingyue Ji:
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging. ICLR 2024
[c80]
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Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization. ICML 2024
[c79]
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Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen:
A Survey on Efficient Federated Learning Methods for Foundation Model Training. IJCAI 2024: 8317-8325
[c78]
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  - conf/infocom/Han0J024
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Pengchao Han, Shiqiang Wang, Yang Jiao, Jianwei Huang:
Federated Learning While Providing Model as a Service: Joint Training and Inference Optimization. INFOCOM 2024: 631-640
[c77]
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Evan Chen, Shiqiang Wang, Christopher G. Brinton:
Taming Subnet-Drift in D2D-Enabled Fog Learning: A Hierarchical Gradient Tracking Approach. INFOCOM 2024: 2438-2447
[c76]
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Divyansh Jhunjhunwala, Neharika Jali, Gauri Joshi, Shiqiang Wang:
Erasure Coded Neural Network Inference via Fisher Averaging. ISIT 2024: 13-18
[c75]
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Herbert Woisetschläger, Alexander Erben, Ruben Mayer, Shiqiang Wang, Hans-Arno Jacobsen:
FLEdge: Benchmarking Federated Learning Applications in Edge Computing Systems. Middleware 2024: 88-102
[c74]
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Cho-Chun Chiu, Tuan Nguyen, Ting He, Shiqiang Wang, Beom-Su Kim, Ki-Il Kim:
Active Learning for WBAN-based Health Monitoring. MobiHoc 2024: 231-240
[c73]
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Guojun Xiong, Gang Yan, Shiqiang Wang, Jian Li:
Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates. MobiHoc 2024: 434-439
[c72]
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Wenzhi Fang, Dong-Jun Han, Evan Chen, Shiqiang Wang, Christopher G. Brinton:
Hierarchical Federated Learning with Multi-Timescale Gradient Correction. NeurIPS 2024
[c71]
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Xiaonan Liu, Shiqiang Wang, Yansha Deng, Arumugam Nallanathan:
Adaptive Model Pruning for Hierarchical Wireless Federated Learning. WCNC 2024: 1-6
2023
[c70]
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  - conf/acssc/00040CJ23
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Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
Rethinking the Data Heterogeneity in Federated Learning. ACSSC 2023: 624-628
[c69]
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Hanjing Wang, Dhiraj Joshi, Shiqiang Wang, Qiang Ji:
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning. CVPR 2023: 12044-12053
[c68]
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Zheyu Chen, Kin K. Leung, Shiqiang Wang, Leandros Tassiulas, Kevin S. Chan, Patrick J. Baker:
Reinforcement Learning for Resource Allocation with Periodic Traffic Patterns. ICC Workshops 2023: 752-757
[c67]
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Bing Luo, Yutong Feng, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Incentive Mechanism Design for Unbiased Federated Learning with Randomized Client Participation. ICDCS 2023: 545-555
[c66]
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Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedExP: Speeding Up Federated Averaging via Extrapolation. ICLR 2023
[c65]
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Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson:
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning. ICML 2023: 3757-3781
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Shiqiang Wang, Jake B. Perazzone, Mingyue Ji, Kevin S. Chan:
Federated Learning with Flexible Control. INFOCOM 2023: 1-10
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Zheyu Chen, Kin K. Leung, Shiqiang Wang, Leandros Tassiulas, Kevin S. Chan, Patrick J. Baker:
Learning Technique to Solve Periodic Markov Decision Process for Network Resource Allocation. MILCOM 2023: 464-470
[c62]
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Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher G. Brinton, Jaekyun Moon:
StableFDG: Style and Attention Based Learning for Federated Domain Generalization. NeurIPS 2023
2022
[c61]
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Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas:
KerGNNs: Interpretable Graph Neural Networks with Graph Kernels. AAAI 2022: 6614-6622
[c60]
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Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD. AAAI 2022: 8548-8556
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Chong Yu, Shuaiqi Shen, Shiqiang Wang, Kuan Zhang, Hai Zhao:
Efficient Multi-Layer Stochastic Gradient Descent Algorithm for Federated Learning in E-health. ICC 2022: 1263-1268
[c58]
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Timothy J. Castiglia, Anirban Das, Shiqiang Wang, Stacy Patterson:
Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data. ICML 2022: 2738-2766
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Georgios Kollias, Theodoros Salonidis, Shiqiang Wang:
Sketch to Skip and Select: Communication Efficient Federated Learning Using Locality Sensitive Hashing. FL@IJCAI 2022: 72-83
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Jake B. Perazzone, Shiqiang Wang, Mingyue Ji, Kevin S. Chan:
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization. INFOCOM 2022: 1449-1458
[c55]
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Bing Luo, Wenli Xiao, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling. INFOCOM 2022: 1739-1748
[c54]
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Shiqiang Wang, Mingyue Ji:
A Unified Analysis of Federated Learning with Arbitrary Client Participation. NeurIPS 2022
2021
[c53]
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Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster:
Online Learning of Facility Locations. ALT 2021: 1002-1050
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Pengchao Han, Jihong Park, Shiqiang Wang, Yejun Liu:
Robustness and Diversity Seeking Data-Free Knowledge Distillation. ICASSP 2021: 2740-2744
[c51]
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Yiwen Han, Shihao Shen, Xiaofei Wang, Shiqiang Wang, Victor C. M. Leung:
Tailored Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud System. INFOCOM 2021: 1-10
[c50]
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Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Cost-Effective Federated Learning Design. INFOCOM 2021: 1-10
[c49]
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Keyang Yu, Qi Li, Dong Chen, Mohammad Rahman, Shiqiang Wang:
PrivacyGuard: Enhancing Smart Home User Privacy. IPSN 2021: 62-76
[c48]
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Zheyu Chen, Kin K. Leung, Shiqiang Wang, Leandros Tassiulas, Kevin Chan:
Robust Solutions to Constrained Optimization Problems by LSTM Networks. MILCOM 2021: 503-508
2020
[c47]
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Tadanobu Inoue, Phongtharin Vinayavekhin, Shu Morikuni, Shiqiang Wang, Tuan Hoang Trong, David Wood, Michiaki Tatsubori, Ryuki Tachibana:
Detection of Anomalous Sounds for Machine Condition Monitoring using Classification Confidence. DCASE 2020: 66-70
[c46]
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Angelo Feraudo, Poonam Yadav, Vadim Safronov, Diana Andreea Popescu, Richard Mortier, Shiqiang Wang, Paolo Bellavista, Jon Crowcroft:
CoLearn: enabling federated learning in MUD-compliant IoT edge networks. EdgeSys@EuroSys 2020: 25-30
[c45]
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Yilei Lin, Ting He, Shiqiang Wang, Kevin S. Chan:
Waypoint-based Topology Inference. ICC 2020: 1-6
[c44]
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Pengchao Han, Shiqiang Wang, Kin K. Leung:
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach. ICDCS 2020: 300-310
[c43]
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Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris:
Communication-efficient k-Means for Edge-based Machine Learning. ICDCS 2020: 595-605
[c42]
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Tiffany Tuor, Shiqiang Wang, Bong Jun Ko, Changchang Liu, Kin K. Leung:
Overcoming Noisy and Irrelevant Data in Federated Learning. ICPR 2020: 5020-5027
[c41]
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Hanlin Lu, Changchang Liu, Shiqiang Wang, Ting He, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris:
Joint Coreset Construction and Quantization for Distributed Machine Learning. Networking 2020: 172-180
[c40]
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Shufan Wang, Jian Li, Shiqiang Wang:
Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice. NeurIPS 2020
[c39]
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  - conf/wcnc/HanWL20
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Pengchao Han, Shiqiang Wang, Kin K. Leung:
Capacity Analysis of Distributed Computing Systems with Multiple Resource Types. WCNC 2020: 1-6
2019
[c38]
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Stephen Pasteris, Fabio Vitale, Kevin S. Chan, Shiqiang Wang, Mark Herbster:
MaxHedge: Maximizing a Maximum Online. AISTATS 2019: 1851-1859
[c37]
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Tadanobu Inoue, Phongtharin Vinayavekhin, Shiqiang Wang, David Wood, Asim Munawar, Bong Jun Ko, Nancy Greco, Ryuki Tachibana:
Shuffling and Mixing Data Augmentation for Environmental Sound Classification. DCASE 2019: 109-113
[c36]
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Hanlin Lu, Ming-Ju Li, Ting He, Shiqiang Wang, Vijaykrishnan Narayanan, Kevin S. Chan:
Robust Coreset Construction for Distributed Machine Learning. GLOBECOM 2019: 1-6
[c35]
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Yilei Lin, Ting He, Shiqiang Wang, Kevin S. Chan, Stephen Pasteris:
Multicast-Based Weight Inference in General Network Topologies. ICC 2019: 1-6
[c34]
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Tiffany Tuor, Shiqiang Wang, Kin K. Leung, Bong Jun Ko:
Online Collection and Forecasting of Resource Utilization in Large-Scale Distributed Systems. ICDCS 2019: 133-143
[c33]
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  - conf/ichi/VhaduriKKWWB19
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Sudip Vhaduri, Theodore G. van Kessel, Bongjun Ko, David Wood, Shiqiang Wang, Thomas Brunschwiler:
Nocturnal Cough and Snore Detection in Noisy Environments Using Smartphone-Microphones. ICHI 2019: 1-7
[c32]
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  - conf/icip/LeeKWLL19
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Wei-Han Lee, Bong Jun Ko, Shiqiang Wang, Changchang Liu, Kin K. Leung:
Exact Incremental and Decremental Learning for LS-SVM. ICIP 2019: 2334-2338
[c31]
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  - conf/infocom/PasterisWH019
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Stephen Pasteris, Shiqiang Wang, Mark Herbster, Ting He:
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems. INFOCOM 2019: 514-522
[c30]
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Vajiheh Farhadi, Fidan Mehmeti, Ting He, Tom La Porta, Hana Khamfroush, Shiqiang Wang, Kevin S. Chan:
Service Placement and Request Scheduling for Data-intensive Applications in Edge Clouds. INFOCOM 2019: 1279-1287
[c29]
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Yilei Lin, Ting He, Shiqiang Wang, Kevin S. Chan, Stephen Pasteris:
Looking Glass of NFV: Inferring the Structure and State of NFV Network from External Observations. INFOCOM 2019: 1774-1782
[c28]
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Aaron K. Baughman, Eduardo Morales, Gary Reiss, Nancy Greco, Stephen Hammer, Shiqiang Wang:
Detection of Tennis Events from Acoustic Data. MMSports@MM 2019: 91-99
[c27]
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  - conf/sensys/AhnGKLMWWW19
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Jae-wook Ahn, Keith Grueneberg, Bong Jun Ko, Wei-Han Lee, Eduardo Morales, Shiqiang Wang, Xiping Wang, David Wood:
Acoustic anomaly detection system: demo abstract. SenSys 2019: 378-379
[c26]
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  - conf/smartcomp/KoW0C19
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Bong Jun Ko, Shiqiang Wang, Ting He, Dave Conway-Jones:
On Data Summarization for Machine Learning in Multi-organization Federations. SMARTCOMP 2019: 63-68
[c25]
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Dave Conway-Jones, Tiffany Tuor, Shiqiang Wang, Kin K. Leung:
Demonstration of Federated Learning in a Resource-Constrained Networked Environment. SMARTCOMP 2019: 484-486
2018
[c24]
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  - conf/fusion/TuorWLC18
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Tiffany Tuor, Shiqiang Wang, Kin K. Leung, Kevin Chan:
Distributed Machine Learning in Coalition Environments: Overview of Techniques. FUSION 2018: 814-821
[c23]
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  - conf/icdcs/0001KWPS18
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Ting He, Hana Khamfroush, Shiqiang Wang, Tom La Porta, Sebastian Stein:
It's Hard to Share: Joint Service Placement and Request Scheduling in Edge Clouds with Sharable and Non-Sharable Resources. ICDCS 2018: 365-375
[c22]
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Tiffany Tuor, Shiqiang Wang, Theodoros Salonidis, Bong Jun Ko, Kin K. Leung:
Demo abstract: Distributed machine learning at resource-limited edge nodes. INFOCOM Workshops 2018: 1-2
[c21]
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Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis, Kin K. Leung, Christian Makaya, Ting He, Kevin Chan:
When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning. INFOCOM 2018: 63-71
2017
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  - conf/cpsweek/VermaKWWB17
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Dinesh C. Verma, Bong Jun Ko, Shiqiang Wang, Xiping Wang, Graham A. Bent:
Audio Analysis as a Control Knob for Social Sensing. SocialSens@CPSWeek 2017: 75-80
[c19]
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  - conf/icassp/WangO17
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Shiqiang Wang, Jorge Ortiz:
Non-negative matrix factorization of signals with overlapping events for event detection applications. ICASSP 2017: 5960-5964
[c18]
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  - conf/icdcs/HeCWC17
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Ting He, Ertugrul N. Ciftcioglu, Shiqiang Wang, Kevin S. Chan:
Location Privacy in Mobile Edge Clouds. ICDCS 2017: 2264-2269
[c17]
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  - conf/uic/PasterisWMCH17
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Stephen Pasteris, Shiqiang Wang, Christian Makaya, Kevin Chan, Mark Herbster:
Data distribution and scheduling for distributed analytics tasks. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017: 1-6
2016
[c16]
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  - conf/mobicom/MachenWLKS16
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Andrew Machen, Shiqiang Wang, Kin K. Leung, Bong Jun Ko, Theodoros Salonidis:
Migrating running applications across mobile edge clouds: poster. MobiCom 2016: 435-436
[c15]
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  - conf/mobihoc/HouZWC16
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I-Hong Hou, Tao Zhao, Shiqiang Wang, Kevin Chan:
Asymptotically optimal algorithm for online reconfiguration of edge-clouds. MobiHoc 2016: 291-300
[c14]
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  - conf/sensys/KoOSTVWWW16
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Bong Jun Ko, Jorge Ortiz, Theodoros Salonidis, Maroun Touma, Dinesh C. Verma, Shiqiang Wang, Xiping Wang, David Wood:
Acoustic Signal Processing for Anomaly Detection in Machine Room Environments: Demo Abstract. BuildSys 2016: 213-214
2015
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Fanzhao Wang, Lei Guo, Shiqiang Wang, Yao Yu, Qingyang Song, Abbas Jamalipour:
Almost as good as single-hop full-duplex: bidirectional end-to-end known interference cancellation. ICC 2015: 1932-1937
[c12]
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  - conf/icc/WangUCHZL15
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Shiqiang Wang, Rahul Urgaonkar, Kevin S. Chan, Ting He, Murtaza Zafer, Kin K. Leung:
Dynamic service placement for mobile micro-clouds with predicted future costs. ICC 2015: 5504-5510
[c11]
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  - conf/milcom/WangCUHL15
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Shiqiang Wang, Kevin S. Chan, Rahul Urgaonkar, Ting He, Kin K. Leung:
Emulation-based study of dynamic service placement in mobile micro-clouds. MILCOM 2015: 1046-1051
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Ertugrul N. Ciftcioglu, Kevin S. Chan, Rahul Urgaonkar, Shiqiang Wang, Ting He:
Security-aware service migration for tactical mobile micro-clouds. MILCOM 2015: 1058-1063
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Shiqiang Wang, Rahul Urgaonkar, Murtaza Zafer, Ting He, Kevin S. Chan, Kin K. Leung:
Dynamic service migration in mobile edge-clouds. Networking 2015: 1-9
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Yue Yang, Shiqiang Wang, Qingyang Song, Lei Guo, Abbas Jamalipour:
Double auction and negotiation for dynamic resource allocation with elastic demands. PIMRC 2015: 1295-1299
2014
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Fanzhao Wang, Qingyang Song, Shiqiang Wang, Lei Guo:
Rate and power adaptation for physical-layer network coding with M-QAM modulation. ICC 2014: 5508-5513
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Shiqiang Wang, Rahul Urgaonkar, Ting He, Murtaza Zafer, Kevin S. Chan, Kin K. Leung:
Mobility-Induced Service Migration in Mobile Micro-clouds. MILCOM 2014: 835-840
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Lu Zhang, Yao Yu, Fei Huang, Qingyang Song, Lei Guo, Shiqiang Wang:
Deadline-aware adaptive packet scheduling and transmission in cooperative wireless networks. PIMRC 2014: 1980-1984
2012
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Yang Huang, Qingyang Song, Shiqiang Wang, Abbas Jamalipour:
Phase-level synchronization for physical-layer network coding. GLOBECOM 2012: 4423-4428
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Shiqiang Wang, Qingyang Song, Lei Guo, Abbas Jamalipour:
Constellation mapping for physical-layer network coding with M-QAM modulation. GLOBECOM 2012: 4429-4434
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Yang Huang, Qingyang Song, Shiqiang Wang, Abbas Jamalipour:
Symbol error rate analysis for M-QAM modulated physical-layer network coding with phase errors. PIMRC 2012: 2003-2008
2010
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Shiqiang Wang, Qingyang Song, Jianxin Feng, Xingwei Wang:
Predicting the link stability based on link connectivity changes in mobile ad hoc networks. WCNIS 2010: 409-414

Parts in Books or Collections

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2022
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Gauri Joshi, Shiqiang Wang:
Communication-Efficient Distributed Optimization Algorithms. Federated Learning 2022: 125-143

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2024
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Rong N. Chang, Carl K. Chang, Jingwei Yang, Zhi Jin, Michael Sheng, Jing Fan, Kenneth Fletcher, Qiang He, Nimanthi L. Atukorala, Hongyue Wu, Shiqiang Wang, Shuiguang Deng, Nirmit Desai, Gopal Pingali, Javid Taheri, K. V. Subramaniam, Feras M. Awaysheh, Kaoutar El Maghaouri, Yingjie Wang:
IEEE International Conference on Edge Computing and Communications, EDGE 2024, Shenzhen, China, July 7-13, 2024. IEEE 2024, ISBN 979-8-3503-6849-9 [contents]

Informal and Other Publications

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2025
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Evan Chen, Jianing Zhang, Shiqiang Wang, Chaoyue Liu, Christopher G. Brinton:
Parameter Tracking in Federated Learning with Adaptive Optimization. CoRR abs/2502.02727 (2025)
[i65]
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Daouda Sow, Herbert Woisetschläger, Saikiran Bulusu, Shiqiang Wang, Hans-Arno Jacobsen, Yingbin Liang:
Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining. CoRR abs/2502.06733 (2025)
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Liangqi Yuan, Dong-Jun Han, Shiqiang Wang, Christopher G. Brinton:
Local-Cloud Inference Offloading for LLMs in Multi-Modal, Multi-Task, Multi-Dialogue Settings. CoRR abs/2502.11007 (2025)
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Hajar Emami-Gohari, Swanand Ravindra Kadhe, Syed Yousaf Shah, Constantin Adam, Abdulhamid Adebayo, Praneet Adusumilli, Farhan Ahmed, Nathalie Baracaldo Angel, Santosh Borse, Yuan Chi Chang, Xuan-Hong Dang, Nirmit Desai, Revital Eres, Ran Iwamoto, Alexei Karve, Yan Koyfman, Wei-Han Lee, Changchang Liu, Boris Lublinsky, Takuya Ohko, Pablo Pesce, Maroun Touma, Shiqiang Wang, Shalisha Witherspoon, Herbert Woisetschlaeger, David Wood, Kun-Lung Wu, Issei Yoshida, Syed Zawad, Petros Zerfos, Yi Zhou, Bishwaranjan Bhattacharjee:
GneissWeb: Preparing High Quality Data for LLMs at Scale. CoRR abs/2502.14907 (2025)
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Jake B. Perazzone, Shiqiang Wang, Mingyue Ji, Kevin S. Chan:
Communication-Efficient Device Scheduling for Federated Learning Using Lyapunov Optimization. CoRR abs/2503.00569 (2025)
2024
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Herbert Woisetschläger, Alexander Isenko, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen:
A Survey on Efficient Federated Learning Methods for Foundation Model Training. CoRR abs/2401.04472 (2024)
[i60]
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Herbert Woisetschläger, Alexander Erben, Bill Marino, Shiqiang Wang, Nicholas D. Lane, Ruben Mayer, Hans-Arno Jacobsen:
Federated Learning Priorities Under the European Union Artificial Intelligence Act. CoRR abs/2402.05968 (2024)
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Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning. CoRR abs/2403.12329 (2024)
[i58]
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Chong Yu, Shuaiqi Shen, Shiqiang Wang, Kuan Zhang, Hai Zhao:
Communication-Efficient Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioning. CoRR abs/2404.10110 (2024)
[i57]
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Bing Luo, Wenli Xiao, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Adaptive Heterogeneous Client Sampling for Federated Learning over Wireless Networks. CoRR abs/2404.13804 (2024)
[i56]
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  - journals/corr/abs-2407-15567
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Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization. CoRR abs/2407.15567 (2024)
[i55]
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Cho-Chun Chiu, Tuan Nguyen, Ting He, Shiqiang Wang, Beom-Su Kim, Ki-Il Kim:
Active Learning for WBAN-based Health Monitoring. CoRR abs/2408.02849 (2024)
[i54]
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Divyansh Jhunjhunwala, Neharika Jali, Gauri Joshi, Shiqiang Wang:
Erasure Coded Neural Network Inference via Fisher Averaging. CoRR abs/2409.01420 (2024)
[i53]
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Evan Chen, Shiqiang Wang, Christopher G. Brinton:
A Hierarchical Gradient Tracking Algorithm for Mitigating Subnet-Drift in Fog Learning Networks. CoRR abs/2409.17430 (2024)
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Wenzhi Fang, Dong-Jun Han, Evan Chen, Shiqiang Wang, Christopher G. Brinton:
Hierarchical Federated Learning with Multi-Timescale Gradient Correction. CoRR abs/2409.18448 (2024)
[i51]
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Ryan Zhang, Herbert Woisetschläger, Shiqiang Wang, Hans-Arno Jacobsen:
MESS+: Energy-Optimal Inferencing in Language Model Zoos with Service Level Guarantees. CoRR abs/2411.00889 (2024)
2023
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Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedExP: Speeding up Federated Averaging Via Extrapolation. CoRR abs/2301.09604 (2023)
[i49]
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  - journals/corr/abs-2304-04824
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Hanjing Wang, Dhiraj Joshi, Shiqiang Wang, Qiang Ji:
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning. CoRR abs/2304.04824 (2023)
[i48]
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  - journals/corr/abs-2304-07981
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Bing Luo, Yutong Feng, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Incentive Mechanism Design for Unbiased Federated Learning with Randomized Client Participation. CoRR abs/2304.07981 (2023)
[i47]
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Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson:
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning. CoRR abs/2305.02219 (2023)
[i46]
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Shihao Shen, Yiwen Han, Xiaofei Wang, Shiqiang Wang, Victor C. M. Leung:
Collaborative Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud Network. CoRR abs/2305.05935 (2023)
[i45]
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Xiaonan Liu, Shiqiang Wang, Yansha Deng, Arumugam Nallanathan:
Adaptive Federated Pruning in Hierarchical Wireless Networks. CoRR abs/2305.09042 (2023)
[i44]
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Shiqiang Wang, Mingyue Ji:
A Lightweight Method for Tackling Unknown Participation Probabilities in Federated Averaging. CoRR abs/2306.03401 (2023)
[i43]
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Guojun Xiong, Gang Yan, Shiqiang Wang, Jian Li:
Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates. CoRR abs/2306.06559 (2023)
[i42]
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Herbert Woisetschläger, Alexander Isenko, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen:
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly. CoRR abs/2310.03150 (2023)
[i41]
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Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher G. Brinton, Jaekyun Moon:
StableFDG: Style and Attention Based Learning for Federated Domain Generalization. CoRR abs/2311.00227 (2023)
[i40]
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Evan Chen, Shiqiang Wang, Christopher G. Brinton:
Taming Subnet-Drift in D2D-Enabled Fog Learning: A Hierarchical Gradient Tracking Approach. CoRR abs/2312.04728 (2023)
[i39]
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Guojun Xiong, Gang Yan, Shiqiang Wang, Jian Li:
DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations. CoRR abs/2312.10815 (2023)
[i38]
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Pengchao Han, Shiqiang Wang, Yang Jiao, Jianwei Huang:
Federated Learning While Providing Model as a Service: Joint Training and Inference Optimization. CoRR abs/2312.12863 (2023)
2022
[i37]
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Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas:
KerGNNs: Interpretable Graph Neural Networks with Graph Kernels. CoRR abs/2201.00491 (2022)
[i36]
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Jake B. Perazzone, Shiqiang Wang, Mingyue Ji, Kevin Chan:
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization. CoRR abs/2201.07912 (2022)
[i35]
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Hanlin Lu, Changchang Liu, Shiqiang Wang, Ting He, Vijay Narayanan, Kevin S. Chan, Stephen Pasteris:
Joint Coreset Construction and Quantization for Distributed Machine Learning. CoRR abs/2204.06652 (2022)
[i34]
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Shiqiang Wang, Mingyue Ji:
A Unified Analysis of Federated Learning with Arbitrary Client Participation. CoRR abs/2205.13648 (2022)
[i33]
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Timothy Castiglia, Anirban Das, Shiqiang Wang, Stacy Patterson:
Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data. CoRR abs/2206.08330 (2022)
[i32]
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Timothy Castiglia, Shiqiang Wang, Stacy Patterson:
Flexible Vertical Federated Learning with Heterogeneous Parties. CoRR abs/2208.12672 (2022)
[i31]
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Shiqiang Wang, Jake B. Perazzone, Mingyue Ji, Kevin S. Chan:
Federated Learning with Flexible Control. CoRR abs/2212.08496 (2022)
2021
[i30]
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Yiwen Han, Shihao Shen, Xiaofei Wang, Shiqiang Wang, Victor C. M. Leung:
Tailored Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud System. CoRR abs/2101.06582 (2021)
[i29]
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  - journals/corr/abs-2102-04282
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Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris:
Communication-efficient k-Means for Edge-based Machine Learning. CoRR abs/2102.04282 (2021)
[i28]
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  - journals/corr/abs-2108-08930
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Anirban Das, Timothy Castiglia, Shiqiang Wang, Stacy Patterson:
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning. CoRR abs/2108.08930 (2021)
[i27]
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  - journals/corr/abs-2109-05411
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Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Cost-Effective Federated Learning in Mobile Edge Networks. CoRR abs/2109.05411 (2021)
[i26]
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  - journals/corr/abs-2112-11256
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Bing Luo, Wenli Xiao, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling. CoRR abs/2112.11256 (2021)
2020
[i25]
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  - journals/corr/abs-2001-04756
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Pengchao Han, Shiqiang Wang, Kin K. Leung:
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach. CoRR abs/2001.04756 (2020)
[i24]
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  - journals/corr/abs-2001-08300
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Tiffany Tuor, Shiqiang Wang, Bong Jun Ko, Changchang Liu, Kin K. Leung:
Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients. CoRR abs/2001.08300 (2020)
[i23]
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  - journals/corr/abs-2002-05808
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Shufan Wang, Jian Li, Shiqiang Wang:
Online Algorithms for Multi-shop Ski Rental with Machine Learned Predictions. CoRR abs/2002.05808 (2020)
[i22]
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  - journals/corr/abs-2002-10610
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Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini:
Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art. CoRR abs/2002.10610 (2020)
[i21]
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  - journals/corr/abs-2007-02801
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Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster:
Online Learning of Facility Locations. CoRR abs/2007.02801 (2020)
[i20]
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  - journals/corr/abs-2007-02977
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Hanlin Lu, Changchang Liu, Ting He, Shiqiang Wang, Kevin S. Chan:
Sharing Models or Coresets: A Study based on Membership Inference Attack. CoRR abs/2007.02977 (2020)
[i19]
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  - journals/corr/abs-2010-12998
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Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
Local Averaging Helps: Hierarchical Federated Learning and Convergence Analysis. CoRR abs/2010.12998 (2020)
[i18]
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  - journals/corr/abs-2011-03749
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Pengchao Han, Jihong Park, Shiqiang Wang, Yejun Liu:
Robustness and Diversity Seeking Data-Free Knowledge Distillation. CoRR abs/2011.03749 (2020)
[i17]
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  - journals/corr/abs-2012-08336
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Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Cost-Effective Federated Learning Design. CoRR abs/2012.08336 (2020)
2019
[i16]
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  - journals/corr/abs-1904-05961
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Hanlin Lu, Ming-Ju Li, Ting He, Shiqiang Wang, Vijay Narayanan, Kevin S. Chan:
Robust Coreset Construction for Distributed Machine Learning. CoRR abs/1904.05961 (2019)
[i15]
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  - journals/corr/abs-1905-09219
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Tiffany Tuor, Shiqiang Wang, Kin K. Leung, Bong Jun Ko:
Online Collection and Forecasting of Resource Utilization in Large-Scale Distributed Systems. CoRR abs/1905.09219 (2019)
[i14]
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  - journals/corr/abs-1906-07055
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Stephen Pasteris, Shiqiang Wang, Mark Herbster, Ting He:
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems. CoRR abs/1906.07055 (2019)
[i13]
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  - journals/corr/abs-1909-12326
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Yuang Jiang, Shiqiang Wang, Bong Jun Ko, Wei-Han Lee, Leandros Tassiulas:
Model Pruning Enables Efficient Federated Learning on Edge Devices. CoRR abs/1909.12326 (2019)
2018
[i12]
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  - journals/corr/abs-1804-05271
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Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis, Kin K. Leung, Christian Makaya, Ting He, Kevin Chan:
When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning. CoRR abs/1804.05271 (2018)
[i11]
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  - journals/corr/abs-1810-11843
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Stephen Pasteris, Fabio Vitale, Kevin Chan, Shiqiang Wang:
MaxHedge: Maximising a Maximum Online with Theoretical Performance Guarantees. CoRR abs/1810.11843 (2018)
2017
[i10]
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  - journals/corr/MachenWLKS17
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Andrew Machen, Shiqiang Wang, Kin K. Leung, Bong Jun Ko, Theodoros Salonidis:
Live Service Migration in Mobile Edge Clouds. CoRR abs/1706.04118 (2017)
[i9]
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  - journals/corr/abs-1709-03133
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Ting He, Ertugrul N. Ciftcioglu, Shiqiang Wang, Kevin S. Chan:
Location Privacy in Mobile Edge Clouds: A Chaff-based Approach. CoRR abs/1709.03133 (2017)
2016
[i8]
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  - journals/corr/WangZL16
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Shiqiang Wang, Murtaza Zafer, Kin K. Leung:
Online Placement of Multi-Component Applications in Edge Computing Environments. CoRR abs/1605.08023 (2016)
[i7]
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  - journals/corr/WangSWW016
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Shiqiang Wang, Qingyang Song, Kailai Wu, Fanzhao Wang, Lei Guo:
End-to-End Known-Interference Cancellation (E2E-KIC) with Multi-Hop Interference. CoRR abs/1605.08029 (2016)
2015
[i6]
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  - journals/corr/WangUCHZL15
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Shiqiang Wang, Rahul Urgaonkar, Kevin S. Chan, Ting He, Murtaza Zafer, Kin K. Leung:
Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs. CoRR abs/1503.02735 (2015)
[i5]
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  - journals/corr/WangUHZCL15
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Shiqiang Wang, Rahul Urgaonkar, Ting He, Murtaza Zafer, Kevin S. Chan, Kin K. Leung:
Mobility-Induced Service Migration in Mobile Micro-Clouds. CoRR abs/1503.05141 (2015)
[i4]
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  - journals/corr/WangUZHCL15
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Shiqiang Wang, Rahul Urgaonkar, Murtaza Zafer, Ting He, Kevin S. Chan, Kin K. Leung:
Dynamic Service Migration in Mobile Edge-Clouds. CoRR abs/1506.05261 (2015)
[i3]
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  - journals/corr/WangGWSJ15
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Fanzhao Wang, Lei Guo, Shiqiang Wang, Qingyang Song, Abbas Jamalipour:
Approaching Single-Hop Performance in Multi-Hop Networks: End-To-End Known-Interference Cancellation (E2E-KIC). CoRR abs/1509.08001 (2015)
2011
[i2]
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  - journals/corr/abs-1108-6132
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Shiqiang Wang, Qingyang Song, Xingwei Wang, Abbas Jamalipour:
Distributed MAC Protocol Supporting Physical-Layer Network Coding. CoRR abs/1108.6132 (2011)
[i1]
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  - journals/corr/abs-1112-0805
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Shiqiang Wang, Qingyang Song, Lei Guo, Abbas Jamalipour:
Physical-Layer Network Coding with M-QAM Modulation. CoRR abs/1112.0805 (2011)

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