… Most machine learning algorithms are supervised. In the following, … learning to solve the
resource allocation problem. … a machine learning framework for resource allocation and …

… a resource allocation strategy for dynamic training and inference of machine learning tasks
… trade-off between energy, delay and learning accuracy. The scenario of interest is composed …

… (operation scheduling, resource allocation) and predictive … Data techniques and machine
learning algorithms to process … for data aggregation, machine learning and intelligent decisions…

… strategy in vehicular networks using machine learning. Therefore, a thorough understanding
of how machine learning algorithms are utilized to offer a dynamic resource allocation in …

… Thus, we can allocate resources in a way that is very … resource allocation in an auction into
machine learning classification or regression problems and propose two resource allocation …

… that can avoid learning the same resource allocation scheme and improve learning efficiency.
The main contribution of this article is a novel resource allocation framework for a MEC-…

… , and machine learning methods used in cloud resource allocation to … how machine learning
methods such as deep neural network (DNN), random forest, and support vector machine (…

… the potential benefits of machine learning for dynamic resource allocation in cloud computing.
… of deep learning models for resource allocation and the exploration of federated learning …

… Some research works have been studied to apply machine learning techniques to optimize
… resource allocation framework was developed to solve the complex resource allocation …

… In this paper, resource allocation and workload distribution for a Canadian healthcare
solution company is presented. The healthcare solution provider has a centralized authority …