… When the training data set is not defined prior to the learning process, the complexity of
finding … learning algorithms which evolve the architecture by itself in online/sequential learning …

… learning algorithms are supervised. In the following, we discuss how to apply supervised
learning to solve the resource allocation … machine learning framework of resource allocation …

… and allocate network resources. This paper investigated how AI algorithms were utilized in
vehicular resource allocation … This paper presents a survey of machine learning algorithms …

… Based on this equation, we propose a fast resource allocation algorithm VIRU in Algorithm
4. The complexity analysis of Algorithm 4 is presented in Theorem V.1 and its convergence …

… The problem can be tackled by designing a reward signal that correlates with the ultimate
objective and the learning algorithm can figure out a decent solution to the problem …

… Then, we explain the use of the learning algorithm to solve (8). … learning algorithm (the
flowchart is shown in Algorithm 1), next, we present the use of the proposed learning algorithm to …

… -of-the-art algorithms, ERAS achieved the minimum Makespan as compared to previous
resource allocation algorithms, while maximizing the Average Resource Utilization (ARU) and …

… The scenario of interest is composed of a set of devices sending a continuous flow of data
to an edge server that extracts relevant information running online learning algorithms, within …

… Motivated by this fact, we model the joint resource scheduling and IoRT data scheduling …
learning framework. To overcome the limitations of traditional reinforcement learning algorithms, …

… learning solutions are not efficient solutions. In the following, we develop a DL-based resource
allocation … joint resource allocation (ie, both power and channel). We use a supervised …