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Kernel Two-Sample Tests
Kernel Two-Sample Tests
3 questions
Difficulty 6-7
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state theorem
Maximum Mean Discrepancy (MMD) is a kernel-based two-sample test statistic. What does it measure?
Hide and think first
A.
The Wasserstein distance, computed via optimal transport between samples
B.
The Kullback-Leibler divergence between two distributions
C.
The distance between two distributions' embeddings in a Reproducing Kernel Hilbert Space (RKHS):
MMD
2
(
P
,
Q
)
=
∥
μ
P
−
μ
Q
∥
H
2
D.
The total variation distance
sup
A
∣
P
(
A
)
−
Q
(
A
)
∣
between distributions
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