In this study, a novel coding scheme called highdensity coding based on high-density codebooks using a genetic local search algorithm is proposed.
To address this, we propose a metric, called an effectivity score, which represents the amount of learning from asynchronous FL.
Phase I clinical trials are designed to test the safety (non-toxicity) of drugs and find the maximum tolerated dose (MTD).
Most of the current methods of subgroup analysis begin with a particular algorithm for estimating individualized treatment effects (ITE) and identify subgroups by maximizing the difference across subgroups of the average treatment effect in each subgroup.
We consider scenarios in which we wish to perform joint scene understanding, object tracking, activity recognition, and other tasks in environments in which multiple people are wearing body-worn cameras while a third-person static camera also captures the scene.
We design a new approach that allows robot learning of new activities from unlabeled human example videos.