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cs.LG2023
Multi-granularity Causal Structure Learning
Jiaxuan Liang, Jun Wang, Guoxian Yu +2
Unveil, model, and comprehend the causal mechanisms underpinning natural phenomena stand as fundamental endeavors across myriad scientific disciplines. Meanwhile, new knowledge eme…
cs.LG2023
Multi-dimensional Fair Federated Learning
Cong Su, Guoxian Yu, Jun Wang +3
Federated learning (FL) has emerged as a promising collaborative and secure paradigm for training a model from decentralized data without compromising privacy. Group fairness and c…
cs.LG2023
Federated Causality Learning with Explainable Adaptive Optimization
Dezhi Yang, Xintong He, Jun Wang +3
Discovering the causality from observational data is a crucial task in various scientific domains. With increasing awareness of privacy, data are not allowed to be exposed, and it…