26 citations · 28 across the 2 of their papers we have counts for
7 papers
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…
Context-Aware Parse Trees
Fangke Ye, Shengtian Zhou, Anand Venkat +8
The simplified parse tree (SPT) presented in Aroma, a state-of-the-art code recommendation system, is a tree-structured representation used to infer code semantics by capturing pro…
ARDA: Automatic Relational Data Augmentation for Machine Learning
Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen +3
Automatic machine learning (\AML) is a family of techniques to automate the process of training predictive models, aiming to both improve performance and make machine learning more…
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…
Neo: A Learned Query Optimizer
Ryan Marcus, Parimarjan Negi, Hongzi Mao +5
Query optimization is one of the most challenging problems in database systems. Despite the progress made over the past decades, query optimizers remain extremely complex component…
Plan-Structured Deep Neural Network Models for Query Performance Prediction
Ryan Marcus, Olga Papaemmanouil
Query performance prediction, the task of predicting the latency of a query, is one of the most challenging problem in database management systems. Existing approaches rely on feat…