Abstract: Graphs play an increasingly important role in various big data applications. However, existing graph data structures cannot simultaneously address the performance bottlenecks caused by the ...

ABSTRACT: In this paper, we consider chessboard graphs in higher dimensions and the number of edges of their corresponding graphs. First, we solve for the number of edges for some of the chessboard ...

Abstract: Graph neural networks (GNNs) rely heavily on graph structures and artificial hyperparameters, which may increase computation and affect performance. Most GNNs use original graphs, but the ...

ABSTRACT: There are hundreds of records in the curriculum of our Language Learning Lab every semester and every record has several important properties. It takes too much time to manage the ...

This paper presents Structure Aware Dense Retrieval (SANTA) model, which encodes user queries and structured data in one universal embedding space for retrieving structured data. SANTA proposes two ...

Data structure for dynamic connectivity in undirected graphs. Supports adding and removing edges and checking whether two vertices are connected (there's a path between them) in polylogarithmic time.

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking and ...

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I'm a software developer and writer, passionate about learning and sharing knowledge and one way I do that is through writing. I'm a software developer and writer, passionate about learning and ...