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2 accepted papers

2024

Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features

ICML 2024spotlight

Random feature (RF) mapping is an attractive and powerful technique for solving large-scale nonparametric regression. Yet, the existing theoretical analysis crucially relies on the i.i.d. assumption that individuals in the data are independent and identically distributed. It is still unclear whether…

Cited by 0SourcePDFScholar