Thispaper presents anefficient multi-scale vision Transformer,called ResT,that capably served as a general-purpose backbone for image recognition.

There exists a stream of papers in the literature on the regularization effect of Dropout for linear models[Wageretal.,2013,MianjyandArora,2019,HelmboldandLong,2015,Cavazzaetal.,2017].

It has achieved great success on different vision-language downstream tasks suchasImage-TextRetrieval,Image-Captioning,andVisualQuestionAnswering.

Standard FL approaches train a unique model for all clients [47, 32, 38, 29, 48].

In this setting, minibatch gradient estimates are exact (namely, exactly 0) on the set of global minimizers since data can be interpolated exactly.