A similarity join combines vectors based on a distance condition. Typically, such algorithms
apply a filter step (by indexing or sorting) and then refine pairs of candidate vectors. In this …

Edit distance similarity search, also called approximate pattern matching, is a fundamental
problem with widespread database applications. The goal of the problem is to preprocess …

Abstract Tensor Core Units (TCUs) are hardware accelerators developed for deep neural
networks, which efficiently support the multiplication of two dense m * m matrices, where m is …

Similarity joins are a basic primitive in data mining. Given two sets of points, we are
interested in reporting all pairs of points whose similarity is above a user-defined threshold …

Large-scale multidimensional array processing is becoming an increasingly important
problem with the rise of big data, scientific data processing, and machine learning …

Locality-sensitive hashing (LSH) has attracted extensive research efforts for approximate
nearest neighbors (NN) search. However, most of these LSH-based index structures fail to …

Advanced data structures is a core course in Computer Science which most graduate
program in Computer Science, Computer Science and Engineering, and other allied …

As data volumes continue to grow, searches in data are becoming increasingly time-
consuming. Classical index structures for neighbor search are no longer sustainable due to …

Similarity joins are a basic primitive in data mining. Given two sets of points, we are
interested in reporting all pairs of points whose similarity is above a user-defined threshold …

As data volumes continue to grow, clustering and outlier detection algorithms are becoming
increasingly time-consuming. Classical index structures for neighbor search are no longer …