Abstract: We develop a novel graph-based trainable framework to maximize the weighted sum energy efficiency (WSEE) for power allocation in wireless communication networks. To address the non-convex ...
Abstract: Group detection is a critical yet challenging task in video-based applications such as surveillance analysis, especially in crowded and dynamic environments where complex pedestrian ...
Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
Heterogeneous Graph Transformer is a graph neural network architecture that can deal with large-scale heterogeneous and dynamic graphs. You can see our WWW 2020 paper “Heterogeneous Graph Transformer” ...
Welcome to the Data Structures and Algorithms (DSA) repository! This repository is dedicated to providing a collection of DSA problems and their solutions in a clear and well-documented format. For me ...
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