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Found 2 papers, 1 papers with code
Matrix Completion with Model-free Weighting
In particular, the proposed method achieves a stronger guarantee than existing work in terms of the scaling with respect to the observation probabilities, under asymptotically heterogeneous missing settings (where entry-wise observation probabilities can be of different orders).
Controlling the False Discovery Rate for Binary Feature Selection via Knockoff
We also provide theoretical results on the power of our variables selection method in a linear regression model or a logistic regression model.
Methodology 62
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