RIT computing students and Professor Rui Li are working on a National Institutes of Health-funded project to use AI in ...

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of large AI models, integration with graph databases is now required. This process ...

Abstract: We demonstrate MITra, a system for synthesizing Multi-Instance graph Traversal algorithms that traverse from multiple source vertices simultaneously over a single thread. Underlying MITra is ...

Embedding-based search outperforms traditional keyword-based methods across various domains by capturing semantic similarity using dense vector representations and approximate nearest neighbor (ANN) ...

So, you want to get good at LeetCode, especially using Java? It’s a common goal for a lot of us trying to land those tech jobs. This guide is all about helping you get there. We’ll go over how to ...

Approximate Nearest Neighbor Search (ANNS) is a fundamental vector search technique that efficiently identifies similar items in high-dimensional vector spaces. Traditionally, ANNS has served as the ...

ABSTRACT: The excessive computational burden encountered in power market analysis has necessitated the need for obtaining reduced equivalent networks that preserve flows along certain selected lines ...

Graph theory is an integral component of algorithm design that underlies sparse matrices, relational databases, and networks. Improving the performance of graph algorithms has direct implications to ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...