… Imitation learning can be further converted into a binary classification problem with … learning
performance, we carefully select the problem-dependent features for the resource allocation …

… can be mitigated by proper resource allocation. Resource allocation for D2D communications
is … use of the machine learning (ML) technique to address the resource allocation in D2D …

… learning (ML) to determine the resource allocations. ML is advantageous in that the actions
taken to find a optimal resource allocation … action and learning from the result. As the agents …

… Simulation results of the learning accelerated optimization method for D2D networks are …
by the accelerated algorithm, while speed refers to the speedup with respect to the original B&B …

… training samples' diversity to ease learning in new environments. This approach … allocation.
The experiment results show that our proposal stabilizes and accelerates the model learning …

… resource allocation. Finally, we discuss key challenges and future research directions of
applying ML/DL for resource allocation … a survey on hardware acceleration techniques for NFV. …

… The accelerator exhibits ultra-low latency performance for … be extended to support hardware
acceleration for other relevant … of the accelerator in a task offloading and resource allocation …

… affect the learning performance. A joint user selection and resource allocation policy towards
… , we consider the joint communication and computation resource allocation in this paper. In …

… can derive an optimal resource allocation solution based on … -based framework for dynamic
resource allocation in a cloud … -based framework for dynamic resource allocation in a cloud …

… of-the-art DRL algorithms for slice resource allocation, and compare it with the traditional 5G
… propose a transfer learningaccelerated DRL-based solution for slice resource allocation. In …