AIDB: a Sparsely Materialized Database for Queries using Machine Learning-Reference-Cited by-同舟云学术

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AIDB: a Sparsely Materialized Database for Queries using Machine Learning

Published:2024-06-09 Issue: Volume:10 Page:23-28
ISSN:
Container-title:Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning
language:
Short-container-title:

Author:

Jin Tengjun¹^ORCID,Mittal Akash¹^ORCID,Mo Chenghao¹^ORCID,Fang Jiahao¹^ORCID,Zhang Chengsong¹^ORCID,Dai Timothy²^ORCID,Kang Daniel¹^ORCID

Affiliation:

1. UIUC

2. Stanford University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3650203.3663329

Reference24 articles.

1. Physical Representation-Based Predicate Optimization for a Visual Analytics Database

2. Michael R Anderson, Michael Cafarella, Thomas F Wenisch, and German Ros. 2019. Predicate Optimization for a Visual Analytics Database. ICDE (2019).

3. Seiden: Revisiting Query Processing in Video Database Systems

4. Favyen Bastani and Samuel Madden. 2022. OTIF: Efficient Tracker Pre-processing over Large Video Datasets. (2022).

5. Oren Ben-Kiki, Clark Evans, and Brian Ingerson. 2009. Yaml ain't markup language (yaml™) version 1.1. Working Draft 2008 5 (2009), 11.

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