162 citations · 378 across the 11 of their papers we have counts for
14 papers
The Duck's Brain: Training and Inference of Neural Networks in Modern Database Engines
Maximilian E. Schüle, Thomas Neumann, Alfons Kemper
Although database systems perform well in data access and manipulation, their relational model hinders data scientists from formulating machine learning algorithms in SQL. Neverthe…
The Case for Learned Spatial Indexes
Varun Pandey, Alexander van Renen, Andreas Kipf +3
Spatial data is ubiquitous. Massive amounts of data are generated every day from billions of GPS-enabled devices such as cell phones, cars, sensors, and various consumer-based appl…
Benchmarking Learned Indexes
Ryan Marcus, Andreas Kipf, Alexander van Renen +5
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 bench…
RadixSpline: A Single-Pass Learned Index
Andreas Kipf, Ryan Marcus, Alexander van Renen +4
Recent research has shown that learned models can outperform state-of-the-art index structures in size and lookup performance. While this is a very promising result, existing learn…
SOSD: A Benchmark for Learned Indexes
Andreas Kipf, Ryan Marcus, Alexander van Renen +4
A groundswell of recent work has focused on improving data management systems with learned components. Specifically, work on learned index structures has proposed replacing traditi…
GeoBlocks: A Query-Cache Accelerated Data Structure for Spatial Aggregation over Polygons
Christian Winter, Andreas Kipf, Christoph Anneser +3
As individual traffic and public transport in cities are changing, city authorities need to analyze urban geospatial data to improve transportation and infrastructure. To that end,…