Single cell messenger RNA sequencing (scRNA-seq) provides a window into transcriptional
landscapes in complex tissues. The recent introduction of droplet based transcriptomics …

Although Locality-Sensitive Hashing (LSH) is a promising approach to similarity search in
high-dimensional spaces, it has not been considered practical partly because its search …

Single-cell RNA sequencing (scRNA-seq) technologies allow researchers to uncover the
biological states of a single cell at high resolution. For computational efficiency and easy …

Efficient similarity search in high-dimensional spaces is important to content-based retrieval
systems. Recent studies have shown that sketches can effectively approximate L 1 distance …

Locally weighted partial least-squares (LW-PLS) is an efficient just-in-time (JIT) modeling
method, which can handle process collinearity, nonlinearity, and time-varying …

ABSTRACT Approximate Nearest Neighbor (ANN) search is a fundamental algorithmic
problem, with numerous applications in many areas of computer science. In this work, we …

Hamming distance has been widely used in many application domains, such as near-
duplicate detection and pattern recognition. We study Hamming distance range query …

This review considers methods and algorithms for fast estimation of distance/similarity
measures between initial data from vector representations with binary or integer-valued …

This article addresses the problem of matching the most similar data objects to a given query
object. We adopt a generic model of similarity that involves the domain of objects and metric …

For approximate nearest neighbor search, graph-based algorithms have shown to offer the
best trade-off between accuracy and search time. We propose the Dynamic Exploration …