Let G be a graph, A(G) be the adjacency matrix of G, and λ(G) the least eigenvalue of A(G). Information is given about the following three quantities: $\lambda_R(G ...

Welcome to my 281 archive! This notes include implementations of basic data structures: union-find sets, unordered_map by hash table, AVL tree, graph represented by adjacency matrix&list and a lot ...

Our goal is to build a high-performance Knowledge Graph tailored for Large Language Models (LLMs), prioritizing exceptionally low latency to ensure fast and efficient information delivery through our ...

This is a preview. Log in through your library . Abstract The emerging field of network science deals with the tasks of modeling, comparing, and summarizing large data sets that describe complex ...

Abstract: Heterogeneous graph representation learning is critical for analyzing complex data structures. Metapaths within this field are vital as they elucidate high-order relationships across the ...

Abstract: Self-supervised hyperspectral image (HSI) clustering remains a fundamental yet challenging task due to the absence of labeled data and the inherent complexity of spatial-spectral ...