@misc{lengerich2021dropout,
author = {Lengerich, Benjamin and Xing, Eric P. and Caruana, Rich},
title = {Dropout as a Regularizer of Interaction Effects},
howpublished = {arXiv},
year = {2021},
month = {October},
abstract = {We examine Dropout through the perspective of interactions. This view provides a symmetry to explain Dropout: given  variables, there are  possible sets of  variables to form an interaction (i.e. ); conversely, the probability an interaction of  variables survives Dropout at rate  is  (decaying with ). These rates effectively cancel, and so Dropout regularizes against higher-order interactions. We prove this perspective analytically and empirically. This perspective of Dropout as a regularizer against interaction effects has several practical implications: (1) higher Dropout rates should be used when we need stronger regularization against spurious high-order interactions, (2) caution should be exercised when interpreting Dropout-based explanations and uncertainty measures, and (3) networks trained with Input Dropout are biased estimators. We also compare Dropout to other regularizers and find that it is difficult to obtain the same selective pressure against high-order interactions.},
url = {http://approjects.co.za/?big=en-us/research/publication/dropout-as-a-regularizer-of-interaction-effects/},
}