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Shiqiang Wang 0001
Person information
- affiliation: IBM Thomas J. Watson Research Center, Yorktown Heights, USA
- affiliation (PhD 2015): Imperial College London, Department of Electrical and Electronic Engineering, UK
Other persons with the same name
- Shiqiang Wang — disambiguation page
- Shiqiang Wang 0002
— Air Force Engineering University, Xi'an, China
- Shiqiang Wang 0003 — Shenzhen University, Shenzhen, China
- Shiqiang Wang 0004 — Nantong University, Nantong, China
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2020 – today
- 2024
- [j31]Bing Luo
Adaptive Heterogeneous Client Sampling for Federated Learning Over Wireless Networks. IEEE Trans. Mob. Comput. 23(10): 9663-9677 (2024) - [j30]Xiaonan Liu
Adaptive Federated Pruning in Hierarchical Wireless Networks. IEEE Trans. Wirel. Commun. 23(6): 5985-5999 (2024) - [c84]Guojun Xiong, Gang Yan, Shiqiang Wang, Jian Li:
DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations. AAAI 2024: 16103-16111 - [c83]Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning. AISTATS 2024: 1612-1620 - [c82]Herbert Woisetschläger
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly. DEEM@SIGMOD 2024: 39-50 - [c81]Hanjing Wang, Shiqiang Wang, Qiang Ji:
Semantic Attribution for Explainable Uncertainty Quantification. Epi UAI 2024: 101-112 - [c80]Shiqiang Wang, Mingyue Ji:
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging. ICLR 2024 - [c79]Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization. ICML 2024 - [c78]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 - [c77]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 - [c76]Evan Chen
Taming Subnet-Drift in D2D-Enabled Fog Learning: A Hierarchical Gradient Tracking Approach. INFOCOM 2024: 2438-2447 - [c75]Divyansh Jhunjhunwala, Neharika Jali, Gauri Joshi, Shiqiang Wang:
Erasure Coded Neural Network Inference via Fisher Averaging. ISIT 2024: 13-18 - [c74]Herbert Woisetschläger
FLEdge: Benchmarking Federated Learning Applications in Edge Computing Systems. Middleware 2024: 88-102 - [c73]Cho-Chun Chiu
Active Learning for WBAN-based Health Monitoring. MobiHoc 2024: 231-240 - [c72]Guojun Xiong
Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates. MobiHoc 2024: 434-439 - [c71]Xiaonan Liu, Shiqiang Wang, Yansha Deng
Adaptive Model Pruning for Hierarchical Wireless Federated Learning. WCNC 2024: 1-6 - [i60]Herbert Woisetschläger
A Survey on Efficient Federated Learning Methods for Foundation Model Training. CoRR abs/2401.04472 (2024) - [i59]Herbert Woisetschläger
Federated Learning Priorities Under the European Union Artificial Intelligence Act. CoRR abs/2402.05968 (2024) - [i58]Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning. CoRR abs/2403.12329 (2024) - [i57]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) - [i56]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) - [i55]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]Divyansh Jhunjhunwala, Neharika Jali, Gauri Joshi, Shiqiang Wang:
Erasure Coded Neural Network Inference via Fisher Averaging. CoRR abs/2409.01420 (2024) - [i53]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) - [i52]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]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
- [j29]Cho-Chun Chiu
Laplacian Matrix Sampling for Communication- Efficient Decentralized Learning. IEEE J. Sel. Areas Commun. 41(4): 887-901 (2023) - [j28]Zheyu Chen
Use Coupled LSTM Networks to Solve Constrained Optimization Problems. IEEE Trans. Cogn. Commun. Netw. 9(2): 304-316 (2023) - [j27]Yuang Jiang
Model Pruning Enables Efficient Federated Learning on Edge Devices. IEEE Trans. Neural Networks Learn. Syst. 34(12): 10374-10386 (2023) - [j26]Shihao Shen
Collaborative Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud Network. IEEE/ACM Trans. Netw. 31(6): 2950-2964 (2023) - [c70]Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
Rethinking the Data Heterogeneity in Federated Learning. ACSSC 2023: 624-628 - [c69]Hanjing Wang, Dhiraj Joshi, Shiqiang Wang, Qiang Ji:
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning. CVPR 2023: 12044-12053 - [c68]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]Bing Luo, Yutong Feng
Incentive Mechanism Design for Unbiased Federated Learning with Randomized Client Participation. ICDCS 2023: 545-555 - [c66]Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedExP: Speeding Up Federated Averaging via Extrapolation. ICLR 2023 - [c65]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 - [c64]Shiqiang Wang, Jake B. Perazzone, Mingyue Ji, Kevin S. Chan:
Federated Learning with Flexible Control. INFOCOM 2023: 1-10 - [c63]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]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 - [i50]Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedExP: Speeding up Federated Averaging Via Extrapolation. CoRR abs/2301.09604 (2023) - [i49]Hanjing Wang, Dhiraj Joshi, Shiqiang Wang, Qiang Ji:
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning. CoRR abs/2304.04824 (2023) - [i48]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]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]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]Xiaonan Liu, Shiqiang Wang, Yansha Deng, Arumugam Nallanathan:
Adaptive Federated Pruning in Hierarchical Wireless Networks. CoRR abs/2305.09042 (2023) - [i44]Shiqiang Wang, Mingyue Ji:
A Lightweight Method for Tackling Unknown Participation Probabilities in Federated Averaging. CoRR abs/2306.03401 (2023) - [i43]Guojun Xiong, Gang Yan, Shiqiang Wang, Jian Li:
Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates. CoRR abs/2306.06559 (2023) - [i42]Herbert Woisetschläger
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly. CoRR abs/2310.03150 (2023) - [i41]Jungwuk Park, Dong-Jun Han
StableFDG: Style and Attention Based Learning for Federated Domain Generalization. CoRR abs/2311.00227 (2023) - [i40]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]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]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
- [j25]Ahmed Imteaj
A Survey on Federated Learning for Resource-Constrained IoT Devices. IEEE Internet Things J. 9(1): 1-24 (2022) - [j24]Anirban Das
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]Hanlin Lu
Communication-Efficient $k$k-Means for Edge-Based Machine Learning. IEEE Trans. Parallel Distributed Syst. 33(10): 2509-2523 (2022) - [c61]Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas:
KerGNNs: Interpretable Graph Neural Networks with Graph Kernels. AAAI 2022: 6614-6622 - [c60]Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD. AAAI 2022: 8548-8556 - [c59]Chong Yu
Efficient Multi-Layer Stochastic Gradient Descent Algorithm for Federated Learning in E-health. ICC 2022: 1263-1268 - [c58]Timothy J. Castiglia, Anirban Das
Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data. ICML 2022: 2738-2766 - [c57]Georgios Kollias, Theodoros Salonidis, Shiqiang Wang:
Sketch to Skip and Select: Communication Efficient Federated Learning Using Locality Sensitive Hashing. FL@IJCAI 2022: 72-83 - [c56]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]Bing Luo
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling. INFOCOM 2022: 1739-1748 - [c54]Shiqiang Wang, Mingyue Ji:
A Unified Analysis of Federated Learning with Arbitrary Client Participation. NeurIPS 2022 - [p1]Gauri Joshi, Shiqiang Wang:
Communication-Efficient Distributed Optimization Algorithms. Federated Learning 2022: 125-143 - [i37]Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas:
KerGNNs: Interpretable Graph Neural Networks with Graph Kernels. CoRR abs/2201.00491 (2022) - [i36]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]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]Shiqiang Wang, Mingyue Ji:
A Unified Analysis of Federated Learning with Arbitrary Client Participation. CoRR abs/2205.13648 (2022) - [i33]Timothy Castiglia, Anirban Das, Shiqiang Wang, Stacy Patterson:
Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data. CoRR abs/2206.08330 (2022) - [i32]Timothy Castiglia, Shiqiang Wang, Stacy Patterson:
Flexible Vertical Federated Learning with Heterogeneous Parties. CoRR abs/2208.12672 (2022) - [i31]Shiqiang Wang, Jake B. Perazzone, Mingyue Ji, Kevin S. Chan:
Federated Learning with Flexible Control. CoRR abs/2212.08496 (2022) - 2021
- [j22]Bing Luo
Cost-Effective Federated Learning in Mobile Edge Networks. IEEE J. Sel. Areas Commun. 39(12): 3606-3621 (2021) - [j21]Shiqiang Wang
Efficient deep learning. Nat. Comput. Sci. 1(3): 181-182 (2021) - [j20]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]Vajiheh Farhadi
Service Placement and Request Scheduling for Data-Intensive Applications in Edge Clouds. IEEE/ACM Trans. Netw. 29(2): 779-792 (2021) - [c53]Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster:
Online Learning of Facility Locations. ALT 2021: 1002-1050 - [c52]Pengchao Han, Jihong Park
Robustness and Diversity Seeking Data-Free Knowledge Distillation. ICASSP 2021: 2740-2744 - [c51]Yiwen Han, Shihao Shen
Tailored Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud System. INFOCOM 2021: 1-10 - [c50]Bing Luo
Cost-Effective Federated Learning Design. INFOCOM 2021: 1-10 - [c49]Keyang Yu, Qi Li, Dong Chen, Mohammad Rahman, Shiqiang Wang:
PrivacyGuard: Enhancing Smart Home User Privacy. IPSN 2021: 62-76 - [c48]Zheyu Chen, Kin K. Leung, Shiqiang Wang, Leandros Tassiulas, Kevin Chan:
Robust Solutions to Constrained Optimization Problems by LSTM Networks. MILCOM 2021: 503-508 - [i30]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]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]Anirban Das, Shiqiang Wang, Stacy Patterson:
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning. CoRR abs/2108.08930 (2021) - [i27]Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Cost-Effective Federated Learning in Mobile Edge Networks. CoRR abs/2109.05411 (2021) - [i26]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
- [j18]Hanlin Lu
Robust Coreset Construction for Distributed Machine Learning. IEEE J. Sel. Areas Commun. 38(10): 2400-2417 (2020) - [j17]Yilei Lin
Looking Glass of NFV: Inferring the Structure and State of NFV Network From External Observations. IEEE/ACM Trans. Netw. 28(4): 1477-1490 (2020) - [c47]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]Angelo Feraudo
CoLearn: enabling federated learning in MUD-compliant IoT edge networks. EdgeSys@EuroSys 2020: 25-30 - [c45]Yilei Lin, Ting He, Shiqiang Wang, Kevin S. Chan:
Waypoint-based Topology Inference. ICC 2020: 1-6 - [c44]Pengchao Han, Shiqiang Wang, Kin K. Leung:
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach. ICDCS 2020: 300-310 - [c43]Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan
Communication-efficient k-Means for Edge-based Machine Learning. ICDCS 2020: 595-605 - [c42]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]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]Shufan Wang, Jian Li, Shiqiang Wang:
Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice. NeurIPS 2020 - [c39]Pengchao Han, Shiqiang Wang, Kin K. Leung:
Capacity Analysis of Distributed Computing Systems with Multiple Resource Types. WCNC 2020: 1-6 - [i25]Pengchao Han, Shiqiang Wang, Kin K. Leung:
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach. CoRR abs/2001.04756 (2020) - [i24]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]Shufan Wang, Jian Li, Shiqiang Wang:
Online Algorithms for Multi-shop Ski Rental with Machine Learned Predictions. CoRR abs/2002.05808 (2020) - [i22]Ahmed Imteaj
Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art. CoRR abs/2002.10610 (2020) - [i21]Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster:
Online Learning of Facility Locations. CoRR abs/2007.02801 (2020) - [i20]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]Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji:
Local Averaging Helps: Hierarchical Federated Learning and Convergence Analysis. CoRR abs/2010.12998 (2020) - [i18]Pengchao Han, Jihong Park
Robustness and Diversity Seeking Data-Free Knowledge Distillation. CoRR abs/2011.03749 (2020) - [i17]Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas:
Cost-Effective Federated Learning Design. CoRR abs/2012.08336 (2020)
2010 – 2019
- 2019
- [j16]Shiqiang Wang
Adaptive Federated Learning in Resource Constrained Edge Computing Systems. IEEE J. Sel. Areas Commun. 37(6): 1205-1221 (2019) - [j15]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]Shiqiang Wang
Dynamic Service Migration in Mobile Edge Computing Based on Markov Decision Process. IEEE/ACM Trans. Netw. 27(3): 1272-1288 (2019) - [c38]Stephen Pasteris, Fabio Vitale, Kevin S. Chan, Shiqiang Wang, Mark Herbster:
MaxHedge: Maximizing a Maximum Online. AISTATS 2019: 1851-1859 - [c37]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]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]Yilei Lin, Ting He, Shiqiang Wang, Kevin S. Chan, Stephen Pasteris:
Multicast-Based Weight Inference in General Network Topologies. ICC 2019: 1-6 - [c34]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]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]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]Stephen Pasteris, Shiqiang Wang, Mark Herbster, Ting He:
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems. INFOCOM 2019: 514-522 - [c30]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]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]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]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]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]Dave Conway-Jones, Tiffany Tuor, Shiqiang Wang, Kin K. Leung:
Demonstration of Federated Learning in a Resource-Constrained Networked Environment. SMARTCOMP 2019: 484-486 - [i16]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]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]Stephen Pasteris, Shiqiang Wang, Mark Herbster, Ting He:
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems. CoRR abs/1906.07055 (2019) - [i13]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
- [j13]Tao Zhao
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]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) - [c24]Tiffany Tuor, Shiqiang Wang, Kin K. Leung, Kevin Chan:
Distributed Machine Learning in Coalition Environments: Overview of Techniques. FUSION 2018: 814-821 - [c23]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]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]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 - [i12]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]Stephen Pasteris, Fabio Vitale, Kevin Chan, Shiqiang Wang:
MaxHedge: Maximising a Maximum Online with Theoretical Performance Guarantees. CoRR abs/1810.11843 (2018) - 2017
- [j11]Shiqiang Wang
Online Placement of Multi-Component Applications in Edge Computing Environments. IEEE Access 5: 2514-2533 (2017) - [j10]Ting He
Location Privacy in Mobile Edge Clouds: A Chaff-Based Approach. IEEE J. Sel. Areas Commun. 35(11): 2625-2636 (2017) - [j9]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) - [c20]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]Shiqiang Wang, Jorge Ortiz:
Non-negative matrix factorization of signals with overlapping events for event detection applications. ICASSP 2017: 5960-5964 - [c18]Ting He, Ertugrul N. Ciftcioglu, Shiqiang Wang, Kevin S. Chan:
Location Privacy in Mobile Edge Clouds. ICDCS 2017: 2264-2269 - [c17]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 - [i10]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]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
- [j8]Fanzhao Wang, Lei Guo
Approaching Single-Hop Performance in Multihop Networks: End-to-End Known-Interference Cancelation (E2E-KIC). IEEE Trans. Veh. Technol. 65(9): 7606-7620 (2016) - [c16]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]I-Hong Hou, Tao Zhao
Asymptotically optimal algorithm for online reconfiguration of edge-clouds. MobiHoc 2016: 291-300 - [c14]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 - [i8]Shiqiang Wang, Murtaza Zafer, Kin K. Leung:
Online Placement of Multi-Component Applications in Edge Computing Environments. CoRR abs/1605.08023 (2016) - [i7]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
- [j7]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) - [c13]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]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]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 - [c10]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 - [c9]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 - [c8]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 - [i6]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]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]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]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) - 2014
- [j6]Qingyang Song, Lei Guo
MAC-centric cross-layer collaboration: a case study on physical-layer network coding. IEEE Wirel. Commun. 21(6): 160-166 (2014) - [c7]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 - [c6]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 - [c5]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 - 2013
- [j5]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]Yang Huang
Synchronous Physical-Layer Network Coding: A Feasibility Study. IEEE Trans. Wirel. Commun. 12(8): 4048-4057 (2013) - 2012
- [j3]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]Qingyang Song, Zhaolong Ning
Link stability estimation based on link connectivity changes in mobile ad-hoc networks. J. Netw. Comput. Appl. 35(6): 2051-2058 (2012) - [c4]Yang Huang
Phase-level synchronization for physical-layer network coding. GLOBECOM 2012: 4423-4428 - [c3]Shiqiang Wang, Qingyang Song, Lei Guo
Constellation mapping for physical-layer network coding with M-QAM modulation. GLOBECOM 2012: 4429-4434 - [c2]Yang Huang
Symbol error rate analysis for M-QAM modulated physical-layer network coding with phase errors. PIMRC 2012: 2003-2008 - 2011
- [j1]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) - [i2]Shiqiang Wang, Qingyang Song, Xingwei Wang, Abbas Jamalipour:
Distributed MAC Protocol Supporting Physical-Layer Network Coding. CoRR abs/1108.6132 (2011) - [i1]Shiqiang Wang, Qingyang Song, Lei Guo, Abbas Jamalipour:
Physical-Layer Network Coding with M-QAM Modulation. CoRR abs/1112.0805 (2011) - 2010
- [c1]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
Coauthor Index
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