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View Code? Open in Web Editor NEWLearning kernels to maximize the power of MMD tests
Home Page: https://arxiv.org/abs/1611.04488
License: BSD 3-Clause "New" or "Revised" License
Learning kernels to maximize the power of MMD tests
Home Page: https://arxiv.org/abs/1611.04488
License: BSD 3-Clause "New" or "Revised" License
Apologies if I'm missing something obvious, but the estimate defined in equation (3) of https://www.jmlr.org/papers/volume13/gretton12a/gretton12a.pdf looks slightly different to the MMD estimate implemented here.
The first term makes sense to me, and subtracting m
accounts for the summation over i != j
(since diagonal of RBF kernel will add to m
). Likewise for second term.
However the third term seems to be missing a factor 1 / (m*n)
.
Lines 44 to 49 in 5c02a92
Is this implementation intended to match the estimate linked above?
Cheers
Hi,
Thanks for sharing. In the tmmd_model.py file, the optimizer seems just trys to minimize the ratio-loss, which should be the approximated test power mentioned in the paper. Shouldn't we increase the test power? I can't find any "-" there. Do I miss anything?
Issue: python package tables is required by pandas, but not automatically installed.
How to reproduce:
python fixed_run.py -n 500 --blobs 1
Error message:
HDFStore requires PyTables, "No module named tables" problem importing
Fix:
pip install tables
fixed the problem for me.
Add requirement tables
to requirements.txt
System:
MacOS 10.11., python 2.7.12
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