Operating critical machine learning models in resource constrained regimes

The accelerated development of machine learning methods, primarily deep learning, are causal to the recent breakthroughs in medical image analysis and computer aided intervention. The resource consumption of deep learning models in terms of amount of training data, compute and energy costs are known to be massive. These large resource costs can be barriers in deploying these models in clinics, globally. To address this, there are cogent efforts within the machine learning community to introduce notions of resource efficiency. For …

analysis compute computer consumption costs cs.ai cs.lg data deep learning development energy energy costs image machine machine learning machine learning models massive medical terms training training data