R. Sahay, S. Nicoll, M. Zhang, T.-Y. Yang, C. Joe-Wong, K. A. Douglas and C. G. Brinton, Predicting Learning Interactions in Social Learning Networks: A Deep Learning Enabled Approach, accepted to IEEE/ACM Transactions on Networking. Preliminary version appeared in IEEE INFOCOM 2017.
T. Kim, S. Sathyanarayana, S. Chen, Y. Im, X. Zhang, S. Ha and C. Joe-Wong, MoDEMS: Optimizing Edge Computing for User Mobility, accepted to IEEE Journal on Selected Areas in Communications. Preliminary versions appeared at IEEE INFOCOM 2022 and as a poster in IEEE IWQoS 2021.
I.-C. Lin, O. Yağan and C. Joe-Wong, Dynamic Coupling Strategy for Interdependent Network Systems Against Cascading Failures, accepted to IEEE Transactions on Network Science and Engineering.
W. Wu, X. Zhang, J. Duan, C. Joe-Wong, Z. Zhou and X. Chen, AdaCoOpt: Leverage the Interplay of Batch Size and Aggregation Frequency for Federated Learning, accepted to IEEE/ACM IWQoS 2023.
Y. Hu, C. Zhang, E. Andert, H. Singh, A. Shrivastava, J. Laudon, Y. Zhou, B. Iannucci and C. Joe-Wong, GiPH: Generalizable Placement Learning for Adaptive Heterogeneous Computing, accepted to MLSys 2023.
X. Liu*, J. Zuo*, H. Xie, C. Joe-Wong and J. C. S. Lui, Variance-Adaptive Algorithm for Probabilistic Maximum Coverage Bandits with General Feedback, accepted to IEEE INFOCOM 2023. *Equal contribution
I.-C. Lin, O. Yağan and C. Joe-Wong, Evaluating the Optimality of Dynamic Coupling Strategies in Interdependent Network Systems, accepted to IEEE ICC 2023.
R. Bostandoost, B. Sun, C. Joe-Wong and M. Hajiesmaili, Near-optimal Online Algorithms for Joint Pricing and Scheduling in EV Charging Networks, accepted to ACM E-Energy 2023.
Y. Yao, M. Mahdi Kamani, E. Cheng, L. Chen, C. Joe-Wong and T. Liu, FedRule: Federated Rule Recommendation System with Graph Neural Networks, ACM/IEEE IoTDI 2023. Preliminary version appeared in the Workshop on Federated Learning: Recent Advances and New Challenges, held in conjunction with NeurIPS 2022.
T. Kim, S. Singh, N. Madaan and C. Joe-Wong, Characterizing Internal Evasion Attacks in Federated Learning, AISTATS 2023. Preliminary version won the Best Student Poster Award at CrossFL 2022.
M. T. Siew, S. Sharma and C. Joe-Wong, ACRE: Actor Critic Reinforcement Learning for Failure-Aware Edge Computing Migrations, CISS 2023.
M. T. Siew, S. Arunasalam, Y. Ruan, Z. Zhu, L. Su, S. Ioannidis, E. Yeh and C. Joe-Wong, Poster Abstract: Fair Training of Multiple Federated Learning Models on Resource Constrained Network Devices, Best Poster Award at ACM/IEEE IPSN 2023.
C. Joe-Wong, S. Ha, Z. Liu, F. M. F. Wong and M. Chiang, Mind Your Own Bandwidth, Fog for 5G and IoT, Wiley, 2016. Preliminary version appeared in IEEE/ACM IWQoS 2015.
Y. Im, C. Joe-Wong, S. Ha, S. Sen, T. Kwon, and M. Chiang, AMUSE: Empowering Users for Cost-Aware Offloading with Throughput-Delay Tradeoffs, IEEE Transactions on Mobile Computing, May 2016. Preliminary version appeared in IEEE INFOCOM 2013 (mini-conference).
C. Joe-Wong, Y. Im, K. Shin and S. Ha, A Performance Analysis of Incentive Mechanisms for Cooperative Computing, IEEE ICDCS 2016.
L. Zheng, C. Joe-Wong, C. Brinton, C. W. Tan, S. Ha and M. Chiang, On the Viability of a Cloud Virtual Service Provider, ACM SIGMETRICS 2016.
S. Sen, C. Joe-Wong, S. Ha and M. Chiang, Time-Dependent Pricing in Mobile Data Plans: Results from a Field Deployment in Alaska, WITS 2016.
Y. Wang, C. Joe-Wong and S. Sen, Congestion Externalities, Content Exclusivity, and Internet Fragmentation, WITS (Workshop on Internet Technologies and Systems) 2016 (poster).
L. Zheng and C. Joe-Wong, Understanding Rollover Data, Smart Data Pricing Workshop 2016.