CRACAU: Byzantine machine learning meets industrial edge computing in industry 5.0 A Du, Y Shen, Q Zhang, L Tseng, M Aloqaily IEEE Transactions on Industrial Informatics 18 (8), 5435-5445, 2021 | 27 | 2021 |
Exact consensus under global asymmetric Byzantine links L Tseng, Q Zhang, S Kumar, Y Zhang 2020 IEEE 40th International Conference on Distributed Computing Systems …, 2020 | 5 | 2020 |
Differentially Private Online-to-batch for Smooth Losses. Q Zhang, H Tran, A Cutkosky NeurIPS, 2022 | 4 | 2022 |
Random scaling and momentum for non-smooth non-convex optimization Q Zhang, A Cutkosky arXiv preprint arXiv:2405.09742, 2024 | 2 | 2024 |
Brief announcement: Computability and anonymous storage-efficient consensus with an abstract mac layer L Tseng, Q Zhang Proceedings of the 2022 ACM Symposium on Principles of Distributed Computing …, 2022 | 2 | 2022 |
Echo-CGC: A communication-efficient byzantine-tolerant distributed machine learning algorithm in single-hop radio network Q Zhang, L Tseng arXiv preprint arXiv:2011.07447, 2020 | 2 | 2020 |
Brief Announcement: Reaching Approximate Consensus When Everyone May Crash L Tseng, Q Zhang, Y Zhang 34th International Symposium on Distributed Computing (DISC 2020), 2020 | 1 | 2020 |
Empirical Tests of Optimization Assumptions in Deep Learning H Tran, Q Zhang, A Cutkosky arXiv preprint arXiv:2407.01825, 2024 | | 2024 |
Private Zeroth-Order Nonsmooth Nonconvex Optimization Q Zhang, H Tran, A Cutkosky arXiv preprint arXiv:2406.19579, 2024 | | 2024 |
Fault-tolerant Consensus in Anonymous Dynamic Network Q Zhang, L Tseng arXiv preprint arXiv:2405.03017, 2024 | | 2024 |
Practical approximate consensus algorithms for small devices in lossy networks Q Zhang, T Bantikyan, L Tseng Proceedings of the 27th Annual International Conference on Mobile Computing …, 2021 | | 2021 |