Recent advancements in learned index structures propose replacing existing index
structures, like B-Trees, with approximate learned models. In this work, we present a unified …

Recently, Machine Learning (ML, for short) has been successfully applied to database
indexing. Initial experimentation on Learned Indexes has demonstrated better search …

Recently, numerous promising results have shown that updatable learned indexes can
perform better than traditional indexes with much lower memory space consumption. But it is …

We address the problem of designing, implementing, and experimenting with compressed
data structures that support rank and select queries over a dictionary of integers. We shine a …

A recent trend in algorithm design consists of augmenting classic data structures with
machine learning models, which are better suited to reveal and exploit patterns and trends …

In recent years, we have seen increased interest in applying machine learning to system
problems. For example, there has been work on applying machine learning to improve …

We investigate the potential of several artificial neural network architectures to be used as
an index on a sorted set of strings, namely, as a mapping from a query string to (an estimate …

A recent trend in algorithm design consists of augmenting classic data structures with
machine learning models, which are better suited to reveal and exploit patterns and trends …

Recent works on learned index open a new direction for the indexing field. The key insight of
the learned index is to approximate the mapping between keys and positions with piece …

The emerging class of instance-optimized systems has shown potential to achieve high
performance by specializing to a specific data and query workloads. Particularly, Machine …