The problem of performing similarity queries on compressed data is considered. We focus
on the quadratic similarity measure, and study the fundamental tradeoff between …

Recently, there has been growing interest in genome sequencing, driven by advancements
in the sequencing technology. Although early sequencing technologies required several …

We consider compression of sequences in a database so that similarity queries can be
performed efficiently in the compressed domain. The fundamental limits for this problem …

We study the problem of compression for the purpose of similarity identification, where
similarity is measured by the mean square Euclidean distance between vectors. While the …

This paper considers the problem of compression for similarity queries [1] and discusses
transform-based compression schemes. Here, the focus is on the tradeoff between the rate …

We study the problem of compressing a source for the goal of answering similarity queries
from the compressed data. Unlike classical compression, here there is no requirement that …

Among many current data processing systems, the objectives are often not the reproduction
of data, but to compute some answers based on the data resulting from queries. The …

The task of similarity identification is to identify items in a database which are similar to a
given query item for a given metric. The identification rate of a compression scheme …

Among many current data processing systems, the objectives are often not the reproduction
of data, but to compute some answers based on the data responding to some queries. The …

Large-scale data generation, acquisition, and processing are happening at every moment in
our society. This thesis explores the opportunities for applying lossy compression methods …