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Tailored Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud System

Jan 17, 2021
Yiwen Han, Shihao Shen, Xiaofei Wang, Shiqiang Wang, Victor C. M. Leung

* IEEE INFOCOM 2021 

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Cost-Effective Federated Learning Design

Dec 15, 2020
Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas

* Accepted in IEEE INFOCOM 2021 

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Robustness and Diversity Seeking Data-Free Knowledge Distillation

Nov 07, 2020
Pengchao Han, Jihong Park, Shiqiang Wang, Yejun Liu


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Local Averaging Helps: Hierarchical Federated Learning and Convergence Analysis

Oct 24, 2020
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji

* 29 pages, 7 figures 

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Sharing Models or Coresets: A Study based on Membership Inference Attack

Jul 06, 2020
Hanlin Lu, Changchang Liu, Ting He, Shiqiang Wang, Kevin S. Chan


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Online Learning of Facility Locations

Jul 06, 2020
Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster


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Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art

Feb 25, 2020
Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini


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Online Algorithms for Multi-shop Ski Rental with Machine Learned Predictions

Feb 13, 2020
Shufan Wang, Jian Li, Shiqiang Wang


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Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients

Jan 22, 2020
Tiffany Tuor, Shiqiang Wang, Bong Jun Ko, Changchang Liu, Kin K. Leung


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Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach

Jan 16, 2020
Pengchao Han, Shiqiang Wang, Kin K. Leung


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Model Pruning Enables Efficient Federated Learning on Edge Devices

Sep 26, 2019
Yuang Jiang, Shiqiang Wang, Bong Jun Ko, Wei-Han Lee, Leandros Tassiulas


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Distilling On-Device Intelligence at the Network Edge

Aug 16, 2019
Jihong Park, Shiqiang Wang, Anis Elgabli, Seungeun Oh, Eunjeong Jeong, Han Cha, Hyesung Kim, Seong-Lyun Kim, Mehdi Bennis

* 7 pages, 6 figures; This work has been submitted to the IEEE for possible publication 

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Online Collection and Forecasting of Resource Utilization in Large-Scale Distributed Systems

May 22, 2019
Tiffany Tuor, Shiqiang Wang, Kin K. Leung, Bong Jun Ko

* Accepted at IEEE International Conference on Distributed Computing Systems (ICDCS) 2019 

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Robust Coreset Construction for Distributed Machine Learning

Apr 11, 2019
Hanlin Lu, Ming-Ju Li, Ting He, Shiqiang Wang, Vijay Narayanan, Kevin S Chan


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MaxHedge: Maximising a Maximum Online with Theoretical Performance Guarantees

Oct 28, 2018
Stephen Pasteris, Fabio Vitale, Kevin Chan, Shiqiang Wang


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Adaptive Federated Learning in Resource Constrained Edge Computing Systems

Aug 02, 2018
Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis, Kin K. Leung, Christian Makaya, Ting He, Kevin Chan

* The current version includes a new convergence bound that is more general than the bound in the previous version. The control algorithm and experimentation results in the current version are new. The new control algorithm can guarantee convergence to zero optimality gap as the resource budget goes to infinity. The experiments are conducted on larger datasets and more results are included 

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