17 citations · 61 across the 10 of their papers we have counts for
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cs.LG2023★ 6 cited
Optimizing Privacy, Utility and Efficiency in Constrained Multi-Objective Federated Learning
Yan Kang, Hanlin Gu, Xingxing Tang +7
Conventionally, federated learning aims to optimize a single objective, typically the utility. However, for a federated learning system to be trustworthy, it needs to simultaneousl…
cs.LG2020★ 1 cited
Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications
Rong Zhu, Andreas Pfadler, Ziniu Wu +6
Structure Learning for Bayesian network (BN) is an important problem with extensive research. It plays central roles in a wide variety of applications in Alibaba Group. However, ex…