2 citations · 4 across the 5 of their papers we have counts for
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stat.ME2021★ 1 cited
PKLM: A flexible MCAR test using Classification
Meta-Lina Spohn, Jeffrey Näf, Loris Michel +1
We develop a fully non-parametric, easy-to-use, and powerful test for the missing completely at random (MCAR) assumption on the missingness mechanism of a dataset. The test compare…
stat.AP2021
Imputation Scores
Jeffrey Näf, Meta-Lina Spohn, Loris Michel +1
Given the prevalence of missing data in modern statistical research, a broad range of methods is available for any given imputation task. How does one choose the `best' imputation…
q-fin.PR2021★ 2 cited
Solving optimal stopping problems with Deep Q-Learning
John Ery, Loris Michel
We propose a reinforcement learning (RL) approach to model optimal exercise strategies for option-type products. We pursue the RL avenue in order to learn the optimal action-value…