Demographic-Independent Fair Graph Learning mitigates group unfairness by minimizing disparities in individual treatment across implicitly identified subgroups, thereby enforcing fairness without requiring explicit demographic information.
Zi-Chong Wang, Zhi-Peng Yin, Mo Sha et al.· Proceedings of the Thirty-Fi...· 4 citations
Following the modular decomposition of industrial recommenders, STAR-CDR introduces three innovations: a CDI Extractor that enhances sequential modeling with domain indicators and other key features, and a CDI Injector that recalibrates activations and enables domain-/scenario-/task-aware expert routing.
Bokai Lin, Nai-Jun Gao, Yucen Gao et al.· Annual International ACM SIG...· 0 citations
This work proposes a novel topology named the Balanced Sparse Tree (BST), which is a topology characterized by symmetric design and sparse connections, motivated by hypergraph theory and Steiner Systems, and demonstrates the superiority of BST over the state-of-the-art in network scale, latency, bandwidth, and cost.
Shaoteng Liu, Dejun Kong, Huitian Wang et al.· Conference on Applications,...· 0 citations
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