| An incentive auction for heterogeneous client selection in federated learning J Pang, J Yu, R Zhou, JCS Lui IEEE Transactions on Mobile Computing 22 (10), 5733-5750, 2022 | 32 | 2022 |
| A truthful procurement auction for incentivizing heterogeneous clients in federated learning R Zhou, J Pang, Z Wang, JCS Lui, Z Li 2021 IEEE 41st International Conference on Distributed Computing Systems …, 2021 | 26 | 2021 |
| Online scheduling algorithm for heterogeneous distributed machine learning jobs R Zhou, J Pang, Q Zhang, C Wu, L Jiao, Y Zhong, Z Li IEEE Transactions on Cloud Computing 11 (2), 1514-1529, 2022 | 22 | 2022 |
| Online scheduling algorithms for unbiased distributed learning over wireless edge networks J Pang, Z Han, R Zhou, H Tan, Y Cao Journal of Systems Architecture 131, 102673, 2022 | 9 | 2022 |
| DPS: Dynamic pricing and scheduling for distributed machine learning jobs in edge-cloud networks R Zhou, N Wang, Y Huang, J Pang, H Chen IEEE Transactions on Mobile Computing 22 (11), 6377-6393, 2022 | 9 | 2022 |
| Automatic dataset construction (adc): Sample collection, data curation, and beyond M Liu, Z Di, J Wei, Z Wang, H Zhang, R Xiao, H Wang, J Pang, H Chen, ... arXiv preprint arXiv:2408.11338, 2024 | 3 | 2024 |
| Online scheduling unbiased distributed learning over wireless edge networks Z Han, R Zhou, J Pang, Y Cao, H Tan 2021 IEEE 27th International Conference on Parallel and Distributed Systems …, 2021 | 3 | 2021 |
| Improving Data Efficiency via Curating LLM-Driven Rating Systems J Pang, J Wei, AP Shah, Z Zhu, Y Wang, C Qian, Y Liu, Y Bao, W Wei ICLR 2025, 2024 | 2 | 2024 |
| Eris: An Online Auction for Scheduling Unbiased Distributed Learning Over Edge Networks J Pang, Z Han, R Zhou, R Zhang, JCS Lui, H Chen IEEE Transactions on Mobile Computing, 2023 | 2 | 2023 |
| Fairness Without Harm: An Influence-Guided Active Sampling Approach J Pang, J Wang, Z Zhu, Y Yao, C Qian, Y Liu NeurIPS 2024, 2024 | 1 | 2024 |
| Towards practical overlay networks for decentralized federated learning Y Hua, J Pang, X Zhang, Y Liu, X Shi, B Wang, Y Liu, C Qian 2024 IEEE 32nd International Conference on Network Protocols (ICNP), 1-11, 2024 | 1 | 2024 |
| Fair Classifiers Without Fair Training: An Influence-Guided Data Sampling Approach J Pang, J Wang, Z Zhu, Y Yao, C Qian, Y Liu arXiv preprint arXiv:2402.12789, 2024 | 1 | 2024 |
| Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning J Pang, N Di, Z Zhu, J Wei, H Cheng, C Qian, Y Liu arXiv preprint arXiv:2502.01968, 2025 | | 2025 |
| LLM Unlearning via Loss Adjustment with Only Forget Data Y Wang, J Wei, CY Liu, J Pang, Q Liu, AP Shah, Y Bao, Y Liu, W Wei ICLR 2025, 2024 | | 2024 |
| Incentivizing Data Collection from Heterogeneous Clients in Federated Learning J Pang, J Wei, C Qian, Y Liu | | |