A popular approach to reduce the size of a massive dataset is to apply efficient online
sampling to the stream of data as it is read or generated. Online sampling routines are …

Scalar field comparison is a fundamental task in scientific visualization. In topological data
analysis, we compare topological descriptors of scalar fields—such as persistence diagrams …

Similarity search based on a distance function in metric spaces is a fundamental problem for
many applications. Queries for similar objects lead to the well-known machine learning task …

We study efficient parallel algorithms for output-sensitive edit distance, achieving
asymptotically better cost bounds than the standard Θ (nm) dynamic programming algorithm …

Approximate string searches have been widely applied in many fields, such as
bioinformatics, text retrieval, search engines, and location-based services (LBS). However …

Approximate nearest neighbor search (ANN) data structures have widespread applications
in machine learning, computational biology, and text processing. The goal of ANN is to …

Edit distance is the most widely used method to quantify similarity between two strings. We
investigate the problem of similarity search under edit distance. Given a collection of …

This article surveys index structures for fast similarity search for objects represented by
symbol strings. Index structures both for exact and approximate searches by edit distance …

The rise of whole-genome shotgun sequencing (WGS) has enabled numerous
breakthroughs in large-scale comparative genomics research. However, the size of genomic …

Background Many bioinformatics applications involve bucketing a set of sequences where
each sequence is allowed to be assigned into multiple buckets. To achieve both high …