AI RESEARCH
Computational-Statistical Trade-off in Kernel Two-Sample Testing with Random Fourier Features
arXiv CS.LG
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ArXi:2407.08976v2 Announce Type: replace-cross Recent years have seen a surge in methods for two-sample testing, among which the Maximum Mean Discrepancy (MMD) test has emerged as an effective tool for handling complex and high-dimensional data. Despite its success and widespread adoption, the primary limitation of the MMD test has been its quadratic-time complexity, which poses challenges for large-scale analysis.