Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …

Due to the increasing privacy concerns and data regulations, training data have been
increasingly fragmented, forming distributed databases of multiple “data silos”(eg, within …

Indexes can improve query-processing performance by avoiding full table scans. Although
traditional indexes (eg, B+-tree) have been widely used, learned indexes are proposed to …

Index structures in memory systems become important to improve the entire system
performance. The promising learned indexes leverage deep-learning models to …

The recently released persistent memory (PM) offers high performance, persistence, and is
cheaper than DRAM. This opens up new possibilities for indexes that operate and persist …

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 …

Non-Volatile Memory (NVM) has emerged as an alternative to next-generation main
memories. Although many tree indices have been proposed for NVM, they generally use B+ …

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